Jobs Data Engineer

We are looking for a senior data engineer with deep Databricks experience to own the data platform behind one of our largest enterprise accounts and lead its migration from AWS to Databricks.

About the role

Data infrastructure is the foundation of everything we deliver. Our models, dashboards, and the decisions our clients make on top of them are only as reliable as the pipelines underneath, which is why we put the platform first.

You will join a small senior team working inside the client's environment. Through the rest of 2026 you will take ownership of the existing pipelines and the architecture around them. From 2027 you will lead the migration to Databricks: designing the target architecture, planning the cutover, and doing the implementation. This is a hands-on engineering role with real architectural authority. You decide how the platform gets built, and then you build it.

You will be the person the team turns to on anything Databricks, working alongside senior machine learning engineers and data scientists who depend on what you deliver.

What you will do:

• Design and build the target Databricks architecture, and plan the migration from the current AWS stack
• Build and maintain production data pipelines: ingestion, transformation, and orchestration
• Own data quality, including the checks and alerts that catch problems before the client does
• Design the data models the analytics and machine learning work sits on
• Support the pipelines you build: monitoring, alerting, and the on-call reality of production data
• Work directly with the client's engineers, and explain technical decisions to people who are not engineers

Requirements:

• Five or more years in data engineering or software development
• At least three years of production Databricks work
• Deep experience with Spark, Delta Lake, and Unity Catalog
• Has planned and executed at least one migration onto Databricks from another platform, and can walk through the challenges
• Expert Python: clean modular code, comfortable with optimization and profiling
• Advanced SQL and relational database work: raw SQL, data modeling, scripted migrations
• Systems design: how storage and compute fit together, end to end pipelines, containerized applications
• Cloud operations on AWS or equivalent: networking, identity and access management, monitoring and alerting, and the domain knowledge for why things break
• Comfortable working inside a client's environment, with their data and their constraints
• Strong written English, and spoken English good enough to present your work
• Available for some overlap with United States working hours

Nice to have:

• Databricks certification
• Deep AWS experience specifically, since that is the platform we are migrating from
• dbt, Airflow, or a similar transformation and orchestration framework
• Machine learning pipeline experience, since models run on top of what you build
• Background in utilities, energy, telecoms, or another regulated industry
• Experience being the senior engineer a client relies on directly

You are:

• Careful with data quality, and you ask when something looks wrong instead of guessing
• A self starter who can turn a general requirement into a specific estimate and a deliverable
• Someone who documents. We write things down, and every number we deliver carries its source
• Comfortable in a small remote team where nobody is checking your hours

About Bennett Data Science

We have spent ten years building predictive analytics and data science for enterprise clients, from some of the largest companies in the world to startups in Silicon Valley. Our engineers sit inside the client's systems and build critical systems. The work ships to production and lands at the bottom line.

What we offer:

• Competitive compensation, reviewed as you grow
• Work from anywhere, with a flexible schedule
• A small senior team, so your work is visible and your decisions are important
• Direct exposure to enterprise clients and the problems they actually have
• Mentorship from senior staff, and the space to grow and mentor others

Pine Software Technology Ltd is a software company specializing in trading technology solutions for regulated brokers and trading firms. We build SaaS products that support electronic trading, brokerage operations, risk management, and financial data analysis. We are looking for a Senior Data Engineer with a strong background in Software Engineering to join our team and lead the unification of our data platform.

Responsibilities:

— Design, build, and maintain scalable batch and streaming data pipelines using PySpark, SQL, and Databricks.
— Implement and manage Change Data Capture (CDC) pipelines to seamlessly ingest data from source systems into the data platform.
— Design and evolve data models using the Medallion Architecture (Bronze, Silver, Gold layers) within the Databricks Lakehouse.
— Provision, configure, and manage cloud infrastructure as code using Terraform.
— Optimize complex SQL queries and Spark jobs to guarantee high performance, reliability, and data quality at scale.
— Take full ownership of pipeline development end-to-end, communicating directly with stakeholders to refine requirements.
— Collaborate closely with Data Analysts, Data Scientists, and product teams as we expand into analytics, dashboards, ML/AI, and real-time processing.
 

Requirements:

— 6+ years of overall software/data engineering experience, with a solid foundation as a Software Engineer who transitioned into data.
— Strong proficiency in Python and SQL.
— Proven track record of designing, building, and scaling ETL/ELT pipelines using PySpark and Databricks.
— Hands-on experience implementing and managing Change Data Capture (CDC) and streaming pipelines.
— Practical knowledge of Databricks Lakehouse, Medallion Architecture, and dimensional data modeling (Star Schema, Kimball).
— Practical experience provisioning and managing infrastructure using Terraform.
— High level of autonomy and accountability — ability to own tasks from ideation through to completion.
— Strong product mindset with a clear understanding of business value.
— English: Upper-Intermediate or higher.
— Ukrainian: Native.
 

Nice to have:

— Financial domain knowledge (capital markets, brokerage, or trading operations).
— Hands-on experience with Apache Beam or Apache Flink.
 

Company offers:

Care from Day One — medical insurance starting from your first day, including dental care, massage services, and professional psychological support.
Work-Life Balance — 25 days of paid vacation + 30 days of paid sick leave
Investment in Your Energy — Partial reimbursement for sports and fitness activities.
Growth & Learning — Coverage for English or Ukrainian language courses and dedicated professional development budget
Knowledge Library — Access to office books and the Kuka online library.
Island Relaxation — Up to 14 days per year at the company villa in Cyprus.
 

Join the Pine Software team, where your talents and aspirations will be recognized. We offer a dynamic work environment, opportunities for professional growth, and support at every step of your career path.
Start your journey with us — apply today and take the first step toward your bright future!
Pine Software is an equal opportunity employer. We encourage applications from candidates of all backgrounds and experiences.
Please note that only shortlisted candidates will be contacted.

Our Customer is a Sweden-based AdTech company specializing in advanced self-serve advertising platforms that automate direct transactions between advertisers and major global publishers. Their solutions improve transparency and operational efficiency in digital advertising and are trusted by globally recognized brands including TripAdvisor, Bloomberg, The Washington Post, Opera, and Dow Jones. The company processes millions of advertising transactions worldwide and is actively investing in AI-driven data capabilities.

PROJECT

The project focuses on building a modern data platform from the ground up with an emphasis on immutable event streams, governed canonical models, semantic layers, and scalable analytics infrastructure. The platform will support analytical workloads, operational data products, AI applications, and future customer-facing data experiences.

As a Principal / Staff Data Platform Engineer, you will own key architectural decisions, define scalable engineering standards, and help deliver the first production-ready version of the platform in a high-scale AdTech environment.

Key Technologies: Apache Iceberg, Spark, Flink, Trino, AWS, Python, Scala, Java, CI/CD, Infrastructure as Code

Job Description

• Lead the technical design and architecture of a modern enterprise-scale data platform
• Define scalable data flows from Iceberg-based event storage into analytical and operational data products
• Evaluate and select technologies for orchestration, transformation, querying, serving, and storage
• Design reusable canonical entities and data models across advertising, campaigns, inventory, billing, and customer domains
• Establish scalable engineering patterns for batch and near-real-time processing
• Build reliable and observable data pipelines for high-volume AdTech workloads
• Implement data quality, lineage, observability, and reconciliation capabilities
• Collaborate with Platform Engineering teams to introduce CI-enforced data contracts and governance standards
• Define tenant isolation, access control, and regional data boundary strategies
• Establish standards for testing, deployment automation, schema evolution, and versioning
• Optimize platform performance, scalability, and infrastructure costs
• Mentor engineers and contribute to engineering excellence across the team
• Partner closely with leadership and cross-functional stakeholders

Qualifications

• 8+ years of experience designing and operating production-grade data platforms
• Strong expertise in distributed data systems and high-volume event-driven architectures
• Deep understanding of modern lakehouse architectures and Apache Iceberg
• Advanced SQL skills and production experience with Python, Java, Scala, or similar languages
• Experience with distributed processing and query technologies such as Spark, Flink, or Trino
• Strong knowledge of data modeling, partitioning strategies, and performance optimization
• Proven experience building batch and near-real-time data pipelines
• Hands-on experience with AWS cloud infrastructure
• Strong understanding of CI/CD pipelines, Infrastructure as Code, and production observability
• Experience implementing data contracts, schema evolution, and data quality frameworks
• Ability to make pragmatic architectural decisions in greenfield environments
• Upper-Intermediate or higher English level
• Strong communication and technical leadership skills
   

Will be a plus
 

• Experience in AdTech or other high-volume event-processing domains
• Experience designing multi-tenant SaaS data architectures
• Familiarity with semantic layer technologies
• Experience supporting both analytics and ML/AI workloads
• Understanding of privacy regulations and data residency requirements

Additional information

What success looks like within your first six months:

• The first production data foundation is running.
• Clear architectural decisions have been made and documented.
• Events entering the data platform have enforceable contracts.
• Core canonical entities exist and are tested.
• Data quality and lineage are observable.
• Other engineers can contribute without needing to understand every implementation detail.

Meet the YozmaTech

YozmaTech isn’t just another tech company – we’re a global team of go-getters, innovators, and A-players helping startups and product companies scale smarter and faster. We build dedicated development teams across 10+ countries, creating strong, long-term partnerships based on trust, transparency, and real impact. Here, every idea counts. We value people who are proactive, open-minded, and ready to grow. If you’re passionate about building meaningful products and want to join a team that feels like family – you’ll feel right at home with us.

Our client is a CX AI platform that enables enterprises to deliver intelligent, automated, and personalized customer experiences across all digital channels. Powered by advanced AI, large language models, and real-time decisioning, the client transforms customer interactions into proactive, context-aware journeys-boosting efficiency, empowering agents, and driving measurable business outcomes at enterprise scale. As a DevOps Engineer, you’ll keep our high-traffic production environments fast, reliable, and secure-and you’ll do it with modern tooling and a strong bias toward automation. We’re looking for someone who treats AI as a force multiplier: curious about new tools, quick to adopt them, and always looking for ways to use AI to eliminate toil, accelerate delivery, and improve operational quality. If you’re passionate about perfecting technology beyond your imagination and want to take part in the revolution of business automation while having a great time doing it – the client is the perfect place for you!

Key Requirements:
🔹 4+ years of experience as a DevOps/SRE/Platform engineer in a high-scale, high-traffic environment;
🔹 4+ years of experience with AWS solutions (EC2, RDS, VPC, S3, Lambda, CloudFront, IAM);
🔹 Hands-on experience with Docker and container orchestration; working knowledge of Kubernetes (EKS) and Helm;
🔹 Experience building CI/CD pipelines and GitOps flows (GitHub Actions, ArgoCD, or equivalents);
🔹 Hands-on experience with scripting languages (Bash/Python), and comfort using AI coding assistants to speed up script generation, tooling, and troubleshooting;
🔹 A demonstrated passion for learning and adopting AI tools to enable and optimize DevOps work-you actively experiment with new tools and bring them into daily practice;
🔹 Experience with both Linux and Windows-based systems, with an understanding of system performance and security;
🔹 Experience with source code management and infrastructure automation (GitHub, and IaC tools);
🔹 Experience managing and troubleshooting cloud and hybrid web environments;
🔹 Experience with database management (MySQL, Redis, Elasticsearch/OpenSearch);
🔹 English – Upper-Intermediate or higher.

Will be plus:
🔹 Experience with AIOps and using AI/ML to predict failures, automate root-cause analysis, and optimize resource allocation;
🔹 Experience with Kubernetes, CloudFormation, Terraform, and NewRelic;
🔹 Experience managing traffic and security with Cloudflare (WAF, Workers, CDN);
🔹 Experience with ELK, IIS, and Directory Services;
🔹 Familiarity with SAST/security scanning tools and shift-left security practices;
🔹 Knowledge of infrastructure as code and familiarity with DevOps cultural principles;

What you will do:
🔹 Build, maintain, and improve our CI/CD pipelines using GitHub Actions to support automated testing, linting, and security gates for daily, low-friction deployments;
🔹 Operate and evolve our GitOps workflow with ArgoCD as the source of truth for cluster state;
🔹 Manage various AWS environments across multiple accounts using Infrastructure as Code, and help optimize edge performance and security;
🔹 Run and troubleshoot Kubernetes (EKS) workloads and contribute to shared Helm charts that abstract complexity for developers while enforcing security and compliance standards;
🔹 Handle technical challenges around performance, scale, and security, and provide root-cause analysis for production incidents;
🔹 Leverage AI tools-coding assistants, AIOps, and automation-to accelerate delivery, script and tooling development, incident diagnosis, and routine operational workflows;
🔹 Continuously identify and automate away repetitive manual work, proposing improvements to reliability, observability, and developer experience;
🔹 Collaborate with the R&D team to optimize service performance, deployment, reliability, failover, and scale;
🔹 Maintain awareness of best industry practices regarding CloudOps, fast deployment, security, and monitoring tools;

Interview stages:
🔹 HR-interview;
🔹 Interview with managers;
🔹 Technical test/interview;
🔹 Final interview with engineering;
🔹 Short HR interview;
🔹 Reference Check;
🔹 Offer.

Why Join Us?

At YozmaTech, we’re self-starters who grow together. Every day, we tackle real challenges for real products – and have fun doing it. We work globally, think entrepreneurially, and support each other like family. We invest in your growth and care about your voice. With us, you’ll always know what you’re working on and why it matters.
From day one, you’ll get:
🔹 Direct access to clients and meaningful products;
🔹 Flexibility to work remotely or from our offices;
🔹 A-team colleagues and a zero-bureaucracy culture;
🔹 Opportunities to grow, lead, and make your mark.

After you apply

We’ll keep it respectful, clear, and personal from start to offer.
You’ll always know what project you’re joining – and how you can grow with us.

Everyone’s welcome

Diversity makes us better. We create a space where you can thrive as you are.

Ready to build something meaningful?

Let’s talk. Your next big adventure might just start here.

We're looking for a Senior Site Reliability Engineer to join our dream team and play a crucial role in building the Infrastructure and DevOps department that powers our innovative, industry-leading products.
 

How will you make a difference?

● Solid experience (3+ years) participating in and contributing to DevOps transformations and infrastructure evolution

● Strong proficiency with Google Cloud Platform (GCP) services, including services like Cloud Run, BigQuery, Cloud Storage or Networking

● Solid experience with Infrastructure as Code tools (e.g., Terraform) for provisioning and managing GCP resources

● Experience with containerization technologies (e.g., Docker)

● Experience with monitoring and logging tools specific to GCP (e.g., Cloud Monitoring, Cloud Logging, Prometheus, Grafana)

● Experience with some programming languages (preferably Typescript, JS, Go or Python)

● Knowledge of version control systems (e.g., Git)

● A strong preference for working in agile and dynamic environments

● Ability to contribute to teamwork and effective collaboration across teams
 

What will you do?

● Implement and refine monitoring, logging, and alerting strategies using GCP's native tools and other relevant solutions

● Maintain and improve Continuous Integration and Continuous Deployment (CI/CD) pipelines

● Collaborate with mobile, web and backend development teams to implement best practices for deployment, performance optimization, and observability of mobile backends on GCP.

● Ensure that security best practices are followed in the configuration of GCP infrastructure and deployment pipelines for mobile backends.

● Maintain detailed technical documentation on deployment architecture, processes, and troubleshooting guides specific to our mobile backend infrastructure on GCP.

● Assist in identifying and implementing improvements to our GCP infrastructure and DevOps processes to enhance efficiency and reliability.

Why join us?
 

🌍 Remote-first & flexible work

• Fully remote working model.
• Access to an office if there is one available in your location.
• Monday–Friday, 40-hour working week.
• Flexible working hours: schedule options between 08:00 and 19:00, including a 1-hour lunch break (the only requirement is a minimum of 5 hours of overlap with the team)

🏖️ Vacation & sick leave

• 15 paid working days of vacation during the first year.
• 20 working days after 2 years.
• 25 working days after 3 years.
• 10 paid sick days per year (for childcare would also be covered), compensated at 100% of salary.
• Public holidays are days off by default.

❤️ Health & family benefits

• Medical insurance or medical insurance compensation.
• Company gifts for:
  • Birthday
  • Wedding
  • Birth of a child
• Paid lunches at the office.
• Family days etc.

📑 FOP / Individual Entrepreneur Support if needed
🔄 Paid Bench period between projects
🤝 No time-tracking software — transparent and trust-based time reporting.
🎁 Referral Program

If you are a Data Engineer who enjoys building reliable data infrastructure, taking ownership of production, solving complex problems, and understanding how data impacts real business decisions, we would love to hear from you.

What We're Looking For

Seeking Alpha is looking for a Senior Data Engineer responsible for designing, building, and maintaining the infrastructure necessary for analyzing large data sets. This individual should be an expert in data management, ETL (extract, transform, load) processes, and data warehousing and should have experience working with various big data technologies, such as Hadoop, Spark, and NoSQL databases. In addition to technical skills, a Senior Data Engineer should have strong communication and collaboration abilities, as they will be working closely with other members of the data and analytics team, as well as other stakeholders, to identify and prioritize data engineering projects and to ensure that the data infrastructure is aligned with the overall business goals and objectives.

The Senior Data Engineer will be engaged with the company as a contractor (Private Entrepreneur).

What You'll Do

• Work closely with data scientists/analytics and other stakeholders to identify and prioritize data engineering projects and to ensure that the data infrastructure is aligned with business goals and objectives
• Design, build and maintain optimal data pipeline architecture for extraction, transformation, and loading of data from a wide variety of data sources, including external APIs, data streams, and data stores. 
• Continuously monitor and optimize the performance and reliability of the data infrastructure, and identify and implement solutions to improve scalability, efficiency, and security
• Stay up-to-date with the latest trends and developments in the field of data engineering, and leverage this knowledge to identify opportunities for improvement and innovation within the organization
• Solve challenging problems in a fast-paced and evolving environment while maintaining uncompromising quality.
• Implement data privacy and security requirements to ensure solutions comply with security standards and frameworks.
• Enhance the team's dev-ops capabilities.

Requirements

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field
• 2+ years of proven experience developing large-scale software using an object-oriented or functional language.
• 5+ years of professional experience in data engineering, focusing on building and maintaining data pipelines and data warehouses
• Strong experience with Spark, Scala, and Python, including the ability to write high-performance, maintainable code
• Experience with AWS services, including EC2, S3, Athena, Kinesis/Firehose Lambda and EMR
• Familiarity with data warehousing concepts and technologies, such as columnar storage, data lakes, and SQL
• Experience with data pipeline orchestration and scheduling using tools such as Airflow
• Strong problem-solving skills and the ability to work independently as well as part of a team
• High-level English - a must. 
• A team player with excellent collaboration skills.

Nice to Have:

• Expertise with Vertica or Redshift, including experience with query optimization and performance tuning
• Experience with machine learning and/or data science projects
• Knowledge of data governance and security best practices, including data privacy regulations such as GDPR and CCPA.
• Knowledge of Spark internals (tuning, query optimization)

Join a Company That Invests in You

Seeking Alpha is the world’s leading community of engaged investors. We’re the go-to destination for investors looking for actionable stock market opinions, real-time market analysis, and unique financial insights. At the same time, we’re also dedicated to creating a workplace where our team thrives. We’re passionate about fostering a flexible, balanced environment with remote work options and an array of perks that make a real difference.

Here, your growth matters. We prioritize your development through ongoing learning and career advancement opportunities, helping you reach new milestones. Join Seeking Alpha to be part of a company that values your unique journey, supports your success, and champions both your personal well-being and professional goals.

Due to continuous growth, our Data Platform is excited to welcome a motivated Data Engineer to help us align reliable marketing, payments, and product data with business goals to drive organizational success.
As a Data Engineer, you’ll play a vital role in building and operating the pipelines that feed daily reporting, attribution, and LTV and be responsible for ingesting data from ad platforms, payment
systems, and product backends into Databricks, orchestrating jobs in Airflow, and keeping silver/gold tables accurate and on time. Working closely with Analytic, Marketing and Data Science teams, you’ll have the opportunity to make a meaningful impact on both our products
and processes.
If you’re passionate about solving complex problems, collaborating across departments, and driving results, this role is perfect for you!
 

As a Data Engineer, you will:

• Build, maintain, and improve data pipelines that support marketing, payments, product analytics, reporting, attribution, and LTV analysis.
• Ingest and transform data from advertising platforms, payment systems, and product backends into the data platform.
• Work with Databricks, including Delta Lake and Unity Catalog, to develop and maintain reliable data models and processing workflows.
• Orchestrate data pipelines and scheduled jobs using Apache Airflow.
• Ensure that silver and gold tables are accurate, reliable, and available on time for downstream users and processes.
• Proactively identify, troubleshoot, and resolve data and pipeline issues to optimize both internal and external processes.
• Take ownership of production data workflows, including scheduled jobs, data quality checks, monitoring, and alerting.
• Investigate failed or delayed production runs and ensure that critical daily processes are restored on time.
• Work with stakeholders across Product, Engineering, Marketing, Analytics, and Data Science to understand requirements, evaluate technical options, and develop appropriate data solutions.
• Balance multiple projects and priorities without compromising quality.
• Develop tools and processes that improve data reliability, efficiency, and usability across the organization.
• Consider business requirements, brand standards, cultural nuances, and regulatory requirements when designing and implementing solutions.
• Contribute to an agile working environment and continuously look for opportunities to improve both technical and operational processes.
   

What will make you stand out

We are looking for someone who combines strong technical expertise with analytical thinking, ownership, and the ability to work effectively in a cross-functional environment.
 

Technical experience:

• Solid professional experience in Data Engineering or a closely related role.
• Strong proficiency in Python and SQL.
• Hands-on experience with Apache Spark.
• Experience working with Databricks, including Delta Lake and/or Unity Catalog.
• Experience with Apache Airflow and workflow orchestration.
• Experience with GCP, particularly Google Cloud Storage (GCS) and BigQuery.
• Experience building, maintaining, and troubleshooting production-grade data pipelines.
• Understanding of data quality, monitoring, alerting, and reliable data delivery.
• Experience working with APIs and integrating external data sources is highly desirable.
   

Nice to have:

• Experience with dbt.
• Experience integrating advertising platforms or marketing data, such as Google Ads or similar platforms.
• Experience working with payment or subscription platforms, such as Stripe, RevenueCat, or similar services.
• Experience working with marketing attribution, subscription data, customer LTV, or related business analytics.
• Experience in a product-oriented or digital business environment.
• Solid understanding of Agile methodologies.
   

Soft skills

• Excellent analytical and problem-solving abilities, with a strategic approach to tackling complex challenges.
• Strong ownership and accountability for production systems and delivered results.
• Ability to investigate issues independently, identify root causes, and implement sustainable solutions.
• Strong collaboration skills and the ability to work seamlessly with cross-functional teams.
• Exceptional communication skills, with the ability to explain technical topics clearly to stakeholders with different levels of technical expertise.
• Ability to manage multiple projects and priorities while maintaining a high standard of quality.
• Curiosity about the business behind the data — including marketing spend, subscriptions, attribution, LTV, and product performance — rather than focusing only on the pipelines that move the data.
• A proactive mindset and willingness to continuously improve processes, tools, and ways of working.
   
• Advanced English proficiency (В2-С1), both written and spoken, for effective communication in an international working environment.
   

Why join us?
 

🌍 Remote-first & flexible work

• Fully remote working model.
• Access to an office if there is one available in your location.
• Monday–Friday, 40-hour working week.
• Flexible working hours: schedule options between 08:00 and 19:00, including a 1-hour lunch break (the only requirement is a minimum of 5 hours of overlap with the team)

🏖️ Vacation & sick leave

• 15 paid working days of vacation during the first year.
• 20 working days after 2 years.
• 25 working days after 3 years.
• 10 paid sick days per year (for childcare would also be covered), compensated at 100% of salary.
• Public holidays are days off by default.

❤️ Health & family benefits

• Medical insurance or medical insurance compensation.
• Company gifts for:
  • Birthday
  • Wedding
  • Birth of a child
• Paid lunches at the office.
• Family days etc.

📑 FOP / Individual Entrepreneur Support if needed
🔄 Paid Bench period between projects
🤝 No time-tracking software — transparent and trust-based time reporting.
🎁 Referral Program

If you are a Data Engineer who enjoys building reliable data infrastructure, taking ownership of production, solving complex problems, and understanding how data impacts real business decisions, we would love to hear from you.

We are looking for a Middle Data Analytics Engineer to build reusable, production-grade pipelines that power our data deals, which are large-scale curated training sets for leading AI labs. You’ll ship engineering solutions with immediate revenue impact and collaborate with some of the world’s largest AI companies. 

 

Responsibilities:

• Work with the business development (BD) team, content experts, data science, and engineering teams to understand customer requirements and available metadata.
• Map customer requirements to our existing metadata and apply data modelling practices to maximize reusability and scalability
• Build DBT models that are capable of querying up to 1B rows efficiently
• Refine DBT models based on visual QA to ensure accurate datasets at scale.
• Propose and implement automated solutions that streamline the curation process and increase scalability.
• Serve as the engineering point of contact, partnering with Business Development to ensure accurate timelines, clear requirements, and manage all technical implementation pieces of the workflow
• Assist the expansion of the data curation workflow to accommodate data science approaches within DBT, streamline the review process to ensure a more rigorous statistical approach with more comprehensive testing

Requirements:

• Strong SQL background with an understanding of query optimization and Snowflake experience.
• DBT experience preferred. 
• Great communication skills.
• 3-5 years of experience in analytics/data engineering.
• Perform code reviews and collaborate with the team to create an optimized ecosystem.

Nice to have:

• BigQuery.
• Python.
• ClickHouse.
• Experience delivering projects in an operational environment. 
• Interest in data science to aid the understanding of customer use cases.
• Interest in photography, music and video creation.

We offer*:

• Flexible working format - remote, office-based or flexible
• A competitive salary and good compensation package
• Personalized career growth
• Professional development tools (mentorship program, tech talks and trainings, centers of excellence, and more)
• Active tech communities with regular knowledge sharing
• Education reimbursement
• Memorable anniversary presents
• Corporate events and team buildings
• Other location-specific benefits

*not applicable for freelancers

Main requirements

Snowflake Experience

The person should be proactive, well-organized, and an effective communicator, able to independently drive tasks forward, keep processes under control, and communicate clearly with the team and stakeholders.

Requirements

Senior Data Enginer

Snowflake — core development

• Writing and maintaining production views, secured views and stored logic in Snowflake
• Understanding of role-based access control: users, roles, GRANTs, warehouse and database entitlement models
• Enough query-tuning instinct to build views over large fact tables without wrecking performance — partition pruning, clustering awareness, avoiding SELECT *

Microsoft SQL Server

• T-SQL development
• Migrating legacy tables, views and stored procedures to Snowflake

Previous ETL Tooling Experience

Bonus Points

BI and semantic layer

• Sigma Computing — connection setup, workbooks, embedding, AI/Cortex configuration. We are rolling Sigma out now and retiring Tableau Desktop.
• Tableau — data source management, extract vs live strategy, extract scheduling and dependency mapping

Documentation and code review

• Producing data-flow and architecture diagrams
• Reviewing SQL/pipeline code to a standard — we have a code review backlog in other areas because there aren’t enough qualified SQL reviewers. A contractor who can act as a second reviewer is disproportionately valuable.

Azure DevOps (aka ADF Pipelines sync’d with Github)

• CI/CD pipelines for database and ADF artefacts, service principal / client secret configuration, release troubleshooting

External API ingestion

• Consuming and loading third-party APIs into the warehouse (e.g. FX/exchange rate feeds), including auth and error handling
• Snowflake Git integration — connecting a Git repository to Snowflake, versioning database objects and deploying from a branch, plus general source-control discipline for SQL and pipeline code
• Snowflake Streamlit — building lightweight in-warehouse data apps as an alternative to a full BI workbook where the audience is small or the use case is operational
• Python for data engineering and Snowpark
• Snowflake Cortex / LLM-in-warehouse features
• dbt or equivalent transformation tooling (not in use today, but relevant if we modernise)

Working attributes we need

• Comfortable being the second pair of hands on a one-person team — takes a ticket end-to-end without daily direction
• Documents as they go; we are explicitly trying to reduce single-person key-man risk
• Cost-aware: several of our decisions are spend-driven, not purely technical

English - Andvanced

We are looking for a Middle Data Analytics Engineer to build reusable, production-grade pipelines that power our data deals, which are large-scale curated training sets for leading AI labs. You’ll ship engineering solutions with immediate revenue impact and collaborate with some of the world’s largest AI companies. 

 

Responsibilities:

• Work with the business development (BD) team, content experts, data science, and engineering teams to understand customer requirements and available metadata.
• Map customer requirements to our existing metadata and apply data modelling practices to maximize reusability and scalability
• Build DBT models that are capable of querying up to 1B rows efficiently
• Refine DBT models based on visual QA to ensure accurate datasets at scale.
• Propose and implement automated solutions that streamline the curation process and increase scalability.
• Serve as the engineering point of contact, partnering with Business Development to ensure accurate timelines, clear requirements, and manage all technical implementation pieces of the workflow
• Assist the expansion of the data curation workflow to accommodate data science approaches within DBT, streamline the review process to ensure a more rigorous statistical approach with more comprehensive testing

Requirements:

• Strong SQL background with an understanding of query optimization and Snowflake experience.
• DBT experience preferred. 
• Great communication skills.
• 3-5 years of experience in analytics/data engineering.
• Perform code reviews and collaborate with the team to create an optimized ecosystem.

Nice to have:

• BigQuery.
• Python.
• ClickHouse.
• Experience delivering projects in an operational environment. 
• Interest in data science to aid the understanding of customer use cases.
• Interest in photography, music and video creation.

About the Role

We are looking for an experienced Lead / Senior Data Engineer to join a high-performing technology team delivering innovative enterprise and AI-driven solutions within a global professional services environment.

The team designs, develops, and deploys modern technology platforms and intelligent tools that support complex business and operational processes. You will work alongside experts in software engineering, data, AI, change management, and project delivery on initiatives ranging from solution design and development to deployment and continuous improvement.

This is an exciting opportunity to work on large-scale, modern cloud and data engineering projects using Azure, Databricks, Spark, Python, and AI-powered technologies.

Technology Stack

• Azure Cloud
• Azure Databricks
• Apache Spark / PySpark
• Microservices Architecture
• .NET 8
• ASP.NET Core
• Python
• MongoDB
• Azure SQL
• Angular
• GitHub and AI-assisted development tools
• LangGraph
• LangChain
• RAG Pipelines
• Multimodal LLMs

Your Responsibilities

• Define and promote engineering best practices and coding standards across the project
• Conduct thorough code reviews to ensure high code quality and adherence to established standards
• Work independently while collaborating closely with cross-functional and distributed teams
• Provide technical guidance and clear direction to team members
• Support the coordination of day-to-day technical activities and delivery priorities
• Communicate regularly with business and project stakeholders
• Design, develop, and maintain robust, scalable, and high-performance Spark applications
• Write clean, maintainable, and efficient code following modern software engineering principles
• Optimize applications and data-processing workflows for performance and scalability
• Ensure efficient and reliable data handling across large-scale data platforms
• Collaborate with engineering, product, data, and business teams to deliver high-quality solutions
• Identify, investigate, and resolve complex technical issues
• Create and maintain comprehensive technical documentation for code, processes, architectures, and workflows

Experience & Technical Skills

• 5+ years of hands-on experience in software development or data engineering
• Practical experience developing SQL stored procedures and migrating legacy SQL logic into Spark SQL or PySpark environments
• Extensive hands-on experience with PySpark and Azure Databricks
• Strong knowledge of Delta Tables, cluster management, and workflow automation
• Proven experience optimizing Apache Spark performance in production environments
• Strong Python programming skills, particularly for complex data processing and manipulation using libraries such as Polars or Pandas
• Solid understanding of columnar data-storage formats, particularly Parquet
• Practical experience working with Delta Lake and modern lakehouse architectures
• Strong expertise in data processing, transformation, and analytical workflows
• Strong analytical and problem-solving skills with a detail-oriented mindset
• Ability to balance engineering standards and structured processes with pragmatic delivery requirements
• Solid understanding of microservices architecture and scalable distributed systems

Nice to Have

• Experience working with Azure Cloud services or other major cloud platforms
• Experience with cloud-based services such as messaging platforms, Data Lake, object storage, caching solutions, and related managed services
• Familiarity with FastAPI
• Experience with containerization and orchestration technologies such as Docker and Kubernetes
• Exposure to AI-driven applications, RAG architectures, LLM orchestration frameworks, or modern generative AI solutions

ABOUT THE ROLE

Due to continuous growth, our Data Platform is excited to welcome a motivated Data Engineer to help us align reliable marketing, payments, and product data with business goals to drive organizational success.
As a Data Engineer, you’ll play a vital role in building and operating the pipelines that feed daily reporting, attribution, and LTV and be responsible for ingesting data from ad platforms, payment
systems, and product backends into Databricks, orchestrating jobs in Airflow, and keeping silver/gold tables accurate and on time. Working closely with Analytic, Marketing and Data Science teams, you’ll have the opportunity to make a meaningful impact on both our products
and processes.
If you’re passionate about solving complex problems, collaborating across departments, and driving results, this role is perfect for you!

YOUR MISSION
As a Data Engineer you will:
● Proactively identify, troubleshoot, and resolve issues to optimize both internal andexternal processes.
● Balance multiple projects without sacrificing quality, aligning your work with brand standards, cultural nuances, and regulatory requirements.
● Engage with diverse stakeholders (e.g., product, engineering, and marketing teams) to gather requirements, evaluate options, and develop tools and processes to support our organization’s goals.

WHAT WILL MAKE YOU STAND OUT FROM THE CROWD
We’re looking for someone with a balance of hard and soft skills who can thrive in a dynamic,
cross-functional environment. Here’s what we’d love to see:
● Excellent analytical and problem-solving abilities, with a strategic approach to tackling challenges.
● Strong collaboration skills for working seamlessly with cross-functional teams.
● Exceptional communication skills for engaging stakeholders across various levels.
● Advanced English proficiency in both speaking and writing, enabling clear and effective interactions.
● Experience with Python, SQL, Spark, Databricks (Unity Catalog / Delta), Apache Airflow, and GCP (GCS, BigQuery); dbt and ads/payments APIs (Google Ads, Stripe, RevenueCat or similar) are a plus. A solid understanding of agile methodologies.
● Comfort owning production: scheduled jobs, data quality checks, alerting, and getting a failed daily run back on time.
● Curiosity about the business behind the tables — marketing spend, subscriptions, and attribution — not only the pipelines that move them.

We are looking for a Senior Data Engineer Consultant to join an AI consulting engagement focused on LLM architecture, RAG, data strategy, and AI platform advisory.
 

This is an advisory role rather than a full-time implementation position. The consultant will work with AI architects, ML engineers, MLOps specialists, and the client’s engineering team to assess the current data landscape, review proposed solutions, and provide practical technical recommendations.
 

Responsibilities
 

Data Strategy
 

• Review the existing enterprise data landscape and available data sources.
   
• Assess data readiness for foundation model training, fine-tuning, evaluation, and RAG.
   
• Recommend data acquisition, prioritization, and preparation approaches.
   
• Advise on multilingual data preparation strategies.
   

Data Pipelines
 

• Review the current ETL/ELT architecture and data processing workflows.
   
• Recommend pipeline designs for model training, inference, and evaluation.
   
• Evaluate orchestration, dataset versioning, and data traceability approaches.
   
• Assess pipeline scalability, reliability, maintainability, and performance.
   

RAG Data Engineering
 

• Review document ingestion architecture for enterprise knowledge bases.
   
• Recommend parsing, chunking, metadata enrichment, embedding, and indexing approaches.
   
• Evaluate vector database and search integration strategies.
   
• Advise on incremental updates, synchronization, access-aware retrieval, and retrieval optimization.
   

Data Governance and Quality
 

• Review data lifecycle management and data governance practices.
   
• Assess PII handling, data masking, retention policies, access control, lineage, and auditability.
   
• Recommend data validation and quality-control frameworks.
   
• Review training and evaluation datasets.
   
• Advise on monitoring data freshness, consistency, completeness, and data drift.
   

Documentation and Consulting
 

• Prepare technical recommendations, architecture assessments, and implementation guidelines.
   
• Review technical documentation, diagrams, and proposed designs.
   
• Participate in architecture reviews, design discussions, and technical workshops.
   
• Conduct knowledge-transfer sessions with the client’s engineering team.
   

Technology Stack
 

Python, SQL, Apache Airflow, Apache Kafka, Hadoop, Apache Superset, n8n, ETL/ELT, RAG Pipelines, Vector Databases, Data Governance, Cloud (AWS, Azure or GCP).
 

Preferred Domain Experience
 

Experience in banking, fintech, financial services, or another highly regulated domain is highly desirable.
 

The ideal candidate should understand domain-specific requirements related to:
 

• sensitive and confidential data;
   
• PII protection and data masking;
   
• role-based access control;
   
• data retention and auditability;
   
• regulatory and compliance requirements;
   
• secure use of enterprise data in AI and LLM solutions.
   

Engagement Details
 

• Engagement model: Part-time consulting.
   
• Workload: Flexible and non-uniform, depending on the current project phase.
   
• Expected activities: Architecture reviews, workshops, document reviews, technical assessments, and advisory sessions.
   
• Duration: Approximately 6 months.
   
• Project type: AI/LLM consulting engagement.
   
• Client interaction: Direct collaboration with the client’s engineering and architecture teams.
   
• Availability: The consultant should be able to join scheduled sessions and provide asynchronous reviews between meetings.
   

An international FinTech company specializing in financial products is looking for a Data Infrastructure Engineer to work remotely.

The company provides ultra-low-latency financial backbone systems to Tier-1 banks in the EU and the U.S. It is certified by more than 100 trading platforms in the Forex market, which account for over 95% of currency liquidity, and offers a comprehensive solution via a single API for both Makers and Takers. These systems enable banks to serve a multitude of algorithmic traders by providing market access and trading, risk management, price adaptation, liquidity aggregation, and more.

The infrastructure product enables international companies and banks to execute instant transactions on global currency exchanges with minimal latency thanks to a custom low-latency gateway. This solution gives clients the advantage of staying ahead of competitors by fractions of a millisecond.

The specialist will develop the foundation for a next-generation FX Trading Analytics platform.

Requirements: experience in building from scratch and maintaining infrastructure for data projects, as well as experience maintaining time-series databases. Experience making decisions regarding data architecture is a plus.

ZentixSoft is looking for a Senior Data Architect! 🚀

Format: Full-Time Outstaffing, long-term remote engagement. You will take full end-to-end ownership of target-state data architecture across multi-cloud environments.
 

💡 Why ZentixSoft?
 💸 Salary Review: A structured system of compensation reviews aligned with your engineering growth. 
⚖️ Work-Life Balance: Sustainable workflows with no senseless overtime, helping you keep your resource fully charged. 
🦾 Trust and Transparency: Zero micromanagement and no invasive time-trackers—we fully trust your professional autonomy. 
🎁 Gifts & Culture: Corporate gifts for holidays, birthdays, and a true team atmosphere where your voice always matters.
 

🧩 Responsibilities:

• Architecture Ownership: Define and own the target-state data architecture across both AWS and Azure cloud environments.
• Platform & Processing Design: Architect enterprise data lakes/warehouses, storage layers, ingestion patterns, and processing frameworks utilizing distributed systems (Spark).
• Governance & Security: Establish enterprise data governance, security, compliance, and access-control standards across both cloud ecosystems.
• Tool & Vendor Evaluation: Evaluate tools/services across AWS and Azure, balancing performance, scalability, maintainability, and cloud costs.
• Technical Leadership & Delivery: Provide architectural oversight and detailed technical documentation to engineering leads during implementation, supporting cloud migration and multi-cloud integration initiatives.

🎓 Requirements:

• Architect Experience: 8+ years in data architecture and engineering, with clear senior/lead-level design responsibility and platform ownership.
• AWS Stack: Deep hands-on architecture experience with AWS (S3, Redshift, Glue, Lake Formation, Athena).
• Azure Stack: Deep hands-on architecture experience with Azure (ADLS, Synapse, Data Factory, Databricks).
• Data Engineering Core: Mastery of data modeling, ETL/ELT pipelines, distributed data processing (Spark), and enterprise data lakes/warehouses.
• Governance & Migrations: Proven track record leading multi-cloud integrations, cloud migrations, and establishing data security and governance standards.
• Communication: Excellent stakeholder communication skills to present architectural decisions to both technical teams and business leadership.
   

➕ Nice to Have:

• Cloud Certifications (AWS Certified Solutions Architect, Azure Solutions Architect Expert).
• Experience with Data Mesh or Domain-Driven Data Architecture.
• Experience in regulated industries (Finance, Healthcare, etc.).
   

📍 Project Details:

⏳ Duration: Long-term (Full-time).

📍 Location: Fully Remote.