Jobs Data Engineer

We are looking for a Team Lead Python Data Engineer to lead the design and operation of large-scale data pipelines that generate property attributes from imagery using our internal AI models.

This role focuses on leading the development of distributed processing systems running on Kubernetes clusters and on-prem GPU infrastructure, capable of processing massive geospatial datasets at national scale.

You will work closely with AI engineers and SaaS platform teams to guide the development of robust pipelines that transform imagery into structured property intelligence used by the insurance and financial industries.

Responsibilities

• Design and build large-scale Python processing pipelines for satellite and street-level imagery

• Develop distributed workloads running on Kubernetes clusters

• Build and maintain orchestration workflows using Airflow

• Design and manage data storage and processing workflows using PostgreSQL

• Integrate large-scale AI inference pipelines running on GPU infrastructure

• Optimize processing performance for massive imagery datasets

• Improve observability, monitoring, and reliability of production pipelines

• Collaborate with AI engineers to support large-scale computer vision inference workflows

• Integrate pipelines with AWS-based services

Requirements

• 7+ years of Python engineering experience

• Strong experience designing distributed data pipelines or large-scale data processing systems

• Experience running workloads on Kubernetes

• Hands-on experience with Airflow or similar orchestration frameworks

• Experience processing large datasets (imagery, geospatial, or other high-volume data)

• Strong understanding of ETL architectures and distributed data systems

Nice to Have

• Experience working with satellite imagery, aerial imagery, or remote sensing datasets

• Experience with GPU-based inference pipelines

• Experience working with on-prem compute clusters

• Experience with C#

We are looking for a Senior Python Data Engineer to design and operate large-scale data pipelines that generate property attributes from imagery using our internal AI models.

This role focuses on building distributed processing systems running on Kubernetes clusters and on-prem GPU infrastructure, capable of processing massive geospatial datasets at national scale.

You will work closely with AI engineers and SaaS platform teams to build robust pipelines that transform imagery into structured property intelligence used by the insurance and financial industries.

Responsibilities

• Design and build large-scale Python processing pipelines for satellite and street-level imagery

• Develop distributed workloads running on Kubernetes clusters

• Build and maintain orchestration workflows using Airflow

• Design and manage data storage and processing workflows using PostgreSQL

• Integrate large-scale AI inference pipelines running on GPU infrastructure

• Optimize processing performance for massive imagery datasets

• Improve observability, monitoring, and reliability of production pipelines

• Collaborate with AI engineers to support large-scale computer vision inference workflows

• Integrate pipelines with AWS-based services

Requirements

• 7+ years of Python engineering experience

• Strong experience designing distributed data pipelines or large-scale data processing systems

• Experience running workloads on Kubernetes

• Hands-on experience with Airflow or similar orchestration frameworks

• Experience processing large datasets (imagery, geospatial, or other high-volume data)

• Strong understanding of ETL architectures and distributed data systems

Nice to Have

• Experience working with satellite imagery, aerial imagery, or remote sensing datasets

• Experience with GPU-based inference pipelines

• Experience working with on-prem compute clusters

• Experience with C#

Our client is an Israeli startup specializing in geodata.

We are looking for a Senior Python Data Engineer to design and operate large-scale data pipelines that generate property attributes from imagery using our internal AI models.

This role focuses on building distributed processing systems running on Kubernetes clusters and on-prem GPU infrastructure, capable of processing massive geospatial datasets at national scale.

You will work closely with AI engineers and SaaS platform teams to build robust pipelines that transform imagery into structured property intelligence used by the insurance and financial industries.

Responsibilities

• Design and build large-scale Python processing pipelines for satellite and street-level imagery

• Develop distributed workloads running on Kubernetes clusters

• Build and maintain orchestration workflows using Airflow

• Design and manage data storage and processing workflows using PostgreSQL

• Integrate large-scale AI inference pipelines running on GPU infrastructure

• Optimize processing performance for massive imagery datasets

• Improve observability, monitoring, and reliability of production pipelines

• Collaborate with AI engineers to support large-scale computer vision inference workflows

• Integrate pipelines with AWS-based services

Requirements

• 7+ years of Python engineering experience

• Strong experience designing distributed data pipelines or large-scale data processing systems

• Experience running workloads on Kubernetes

• Hands-on experience with Airflow or similar orchestration frameworks

• Experience processing large datasets (imagery, geospatial, or other high-volume data)

• Strong understanding of ETL architectures and distributed data systems

Nice to Have

• Experience working with satellite imagery, aerial imagery, or remote sensing datasets

• Experience with GPU-based inference pipelines

• Experience working with on-prem compute clusters

• Experience with C#

Our client is an Israeli startup specializing in geodata.

Team Lead Python Data Engineer (Python)

Our client is an Israeli startup specializing in geodata.

We are looking for a Team Lead Python Data Engineer to lead the design and operation of large-scale data pipelines that generate property attributes from imagery using our internal AI models.

This role focuses on leading the development of distributed processing systems running on Kubernetes clusters and on-prem GPU infrastructure, capable of processing massive geospatial datasets at national scale.

You will work closely with AI engineers and SaaS platform teams to guide the development of robust pipelines that transform imagery into structured property intelligence used by the insurance and financial industries.

Responsibilities

• Design and build large-scale Python processing pipelines for satellite and street-level imagery

• Develop distributed workloads running on Kubernetes clusters

• Build and maintain orchestration workflows using Airflow

• Design and manage data storage and processing workflows using PostgreSQL

• Integrate large-scale AI inference pipelines running on GPU infrastructure

• Optimize processing performance for massive imagery datasets

• Improve observability, monitoring, and reliability of production pipelines

• Collaborate with AI engineers to support large-scale computer vision inference workflows

• Integrate pipelines with AWS-based services

Requirements

• 7+ years of Python engineering experience

• Strong experience designing distributed data pipelines or large-scale data processing systems

• Experience running workloads on Kubernetes

• Hands-on experience with Airflow or similar orchestration frameworks

• Experience processing large datasets (imagery, geospatial, or other high-volume data)

• Strong understanding of ETL architectures and distributed data systems

Nice to Have

• Experience working with satellite imagery, aerial imagery, or remote sensing datasets

• Experience with GPU-based inference pipelines

• Experience working with on-prem compute clusters

• Experience with C#

Our client is an Israeli startup specializing in geodata.

Requirements

Total of 5+ years of development/design experience with a minimum of 5 years experience in Big Data technologies on-prem or on cloud.
Experience with architecting, building, implementing and managing Big Data platforms On Cloud, covering ingestion (Batch and Real time), processing (Batch and Realtime), Polyglot Storage, Data Analytics and Data Access
Good understanding of Data Governance, Data Security, Data Compliance, Data Quality, Meta Data Management, Master Data Management, Data Catalog
Proven understanding and demonstrable implementation experience of big data platform technologies on cloud (AWS and Azure) including surrounding services like IAM, SSO, Cluster monitoring, Log Analytics etc
Experience working with Enterprise Data Warehouse technologies, Multi-Dimensional Data Modeling, Data Architectures or other work related to the construction of enterprise data assets
Strong Experience implementing ETL/ELT processes and building data pipelines including workflow management, job scheduling and monitoring
Experience building stream-processing systems, using solutions such as Apache Spark, Databricks, Kafka etc…
Experience with Spark/Databricks technology is a must
Experience with Big Data querying tools
Solid skills in Python
Strong experience with data modelling and schema design
Strong SQL programming background
Excellent interpersonal and teamwork skills
Experience to drive solution/enterprise-level architecture, collaborate with other tech leads
Strong problem solving, troubleshooting and analysis skills
Experience working in a geographically distributed team
Experience with leading and mentorship of other team members
Good knowledge of Agile Scrum
Good communication skills

 #LI-OE1

#LI-Remote

Job responsibilities

Work directly with the Client teams to understand the requirements/needs and rapidly prototype data and analytics solutions based upon business requirements
Design, implement and manage large scale data platform/applications including ingestion, processing, storage, data access, data governance capabilities and related infrastructure
Support Design and development of solutions for the deployment of data analytics notebooks, tools, dashboards and reports to various stakeholders
Communication with Product/DevOps/Development/QA team
Architect data pipelines and ETL/ELT processes to connect with various data sources
Design and maintain enterprise data warehouse models
Take part in the performance optimization processes
Guide on research activities (PoC) if necessary
Manage cloud based data & analytics platform
Establishing best practices with CICD under BigData scope

What we offer

Culture of caring. At GlobalLogic, we prioritize a culture of caring. Across every region and department, at every level, we consistently put people first. From day one, you’ll experience an inclusive culture of acceptance and belonging, where you’ll have the chance to build meaningful connections with collaborative teammates, supportive managers, and compassionate leaders. 

Learning and development. We are committed to your continuous learning and development. You’ll learn and grow daily in an environment with many opportunities to try new things, sharpen your skills, and advance your career at GlobalLogic. With our Career Navigator tool as just one example, GlobalLogic offers a rich array of programs, training curricula, and hands-on opportunities to grow personally and professionally.

Interesting & meaningful work. GlobalLogic is known for engineering impact for and with clients around the world. As part of our team, you’ll have the chance to work on projects that matter. Each is a unique opportunity to engage your curiosity and creative problem-solving skills as you help clients reimagine what’s possible and bring new solutions to market. In the process, you’ll have the privilege of working on some of the most cutting-edge and impactful solutions shaping the world today.

Balance and flexibility. We believe in the importance of balance and flexibility. With many functional career areas, roles, and work arrangements, you can explore ways of achieving the perfect balance between your work and life. Your life extends beyond the office, and we always do our best to help you integrate and balance the best of work and life, having fun along the way!

High-trust organization. We are a high-trust organization where integrity is key. By joining GlobalLogic, you’re placing your trust in a safe, reliable, and ethical global company. Integrity and trust are a cornerstone of our value proposition to our employees and clients. You will find truthfulness, candor, and integrity in everything we do.

HI! 
SFORS trades in the global financial markets and are among the key proprietary trading players and pre-market trading leaders.
Our company owes its 20 years of success in the stock market to constantly investing in talent development, trading technologies, progressive risk management models, and effective trading strategies - all of which drive trader success.
SFORS operates exclusively with proprietary funds, without any third-party investments.

We are looking for a Data Engineer to design, build, and maintain scalable data pipelines and infrastructure. You will ensure reliable data flow across systems, support strong data modeling practices, uphold data security standards, and enable analytics and machine learning teams with high‑quality, well‑structured data.

Key Responsibilities:

• Build and maintain ELT pipelines for batch and streaming data
• Develop and optimize data warehouses, data lakes, and lakehouse architectures
• Ensure data quality, governance, and security standards are implemented and maintained
• Collaborate with analysts, data scientists, and engineering teams to deliver clean, reliable datasets
• Monitor and improve data architecture performance, and cost efficiency

Core Skills & Technologies:

• Programming: SQL / Python / Scala is a plus
• Cloud Platforms: Google Cloud Platform (GCP) / Microsoft Azure
• Data Integration & Orchestration: Apache Airflow / Azure Data Factory
• Messaging / Ingestion: Apache Kafka / Google Pub/Sub / Azure Event Hubs
• Data Processing: Apache Spark / Databricks / Dataflow / Azure Stream Analytics
• Data Analytics Platforms: BigQuery / Azure Synapse Analytics / Microsoft Fabric
• Data Modeling & Architecture
  • Experience with data modeling tools, like DBT
  • Knowledge of data warehousing best practices
  • Familiarity with Data lake / lakehouse architectures
• DevOps & Infrastructure
  • CI/CD for data pipelines
  • Version control
  • Infrastructure as Code (i.e. Terraform) is a plus
  • Containerized deployment is a plus
• AI/ML (Nice to Have)
  • Experience with Agent Development Kit (ADK)
  • Experience building data pipelines for ML use cases

  • Familiarity with tools such as BigQuery ML and Vertex AI

     

Language requirements:

• English - Upper-Intermediate or higher
• Ukrainian - Professional fluency (would be an advantage)

What We Offer:

• Competitive salary package
• Professional growth and learning opportunities
• Supportive and collaborative work environment
• SFORS invests in talent development through training programs, sports, leisure, and psychological support.

Hi!

We are Boosta — a holding tech company that creates, scales, and invests in digital businesses with global potential. Today, over 700 specialists from all around the world collaborate with us, and millions of users enjoy our products and services.

We are looking for a Data Engineer to join Boosta’s service team, which provides design, development, content, and IT infrastructure creation & support services for the holding’s projects.

Key facts about Webtech:

• 60+ skilled professionals;
• 300+ projects per year;
• diverse project portfolio.

As a Data Engineer, you will:

• Design, build, and maintain reliable ETL / ELT data pipelines.
• Ingest data from multiple internal and external sources (APIs, event-based systems).
• Ensure data freshness, availability, and pipeline reliability using orchestration tools (Airflow or similar).
• Implement automated data quality checks and monitor data consistency.
• Prepare clean, analytics-ready datasets for Analysts and Data Scientists.
• Work closely with both technical and non-technical stakeholders (Analytics, Product, Finance, Business) — a significant part of the role involves communication, alignment on requirements, data definitions, and explaining data limitations or inconsistencies.
• Maintain clear documentation and monitor data infrastructure costs.

We value specialists who:

• Advanced SQL.
• Python for data pipelines and integrations.
• Experience with modern cloud data warehouses.
• Hands-on experience with workflow orchestration tools (Airflow or similar).
• Experience with API-based data ingestion.
• Strong understanding of data quality, data reliability, and data delivery best practices.
• Experience with Git and basic containerization (e.g. Docker).

Nice to Have:

• Experience with affiliate, marketing, or performance data.
• Event-based or postback-driven data ingestion.
• Experience optimizing cloud data infrastructure costs.
• Experience with GCP.

Your journey with us:

• Step 1. Pre-screen.
• Step 2. Interview.
• Step 3. Test Task.
• Step 4. Second Interview.
• Step 5. Reference check.
• Step 6. Job Offer!

What you’ll get from working with us:

• Support for your career growth: compensation for external courses and conferences, access to our corporate library.
• Flexible schedule: you can start your working day anytime between 8:00–11:00 Kyiv time.
• Work location of your choice: Kyiv office, coworking in Lviv or Warsaw, or fully remote.
• 28 working days of paid vacation per year, up to 30 days of sick leave with medical confirmation, plus all state holidays.
• Care for your health: medical insurance and compensation for psychologist sessions.
• Social initiatives: Ukrainian Victory Support program and other important projects.
• Regular team-building activities, online or offline.

Senior Data Engineer

About the Company

Our company is a leading technology provider specializing in data-driven solutions that help businesses transform their operations and generate insights from complex datasets. We work with clients across various industries globally, building scalable and efficient data infrastructure that powers business intelligence and analytics.

Work Format

• 100% Remote Work
• Flexible schedule
• Opportunity to work from any location

Responsibilities

• Design, build, and maintain scalable data processing pipelines and ETL workflows
• Develop data models and implement data warehousing solutions
• Create and optimize database schemas and queries for performance
• Integrate diverse data sources and ensure data quality and consistency
• Implement and manage big data processing systems using modern technologies
• Collaborate with data scientists and analysts to understand data requirements and provide solutions
• Build data monitoring and validation systems to ensure data integrity
• Design and implement data governance practices and documentation
• Optimize data architecture for cost, reliability, and performance
• Participate in code reviews and mentor junior engineers

Requirements

Mandatory

• 5+ years of experience in data engineering roles
• Strong expertise in SQL and database design (SQL Server, PostgreSQL, MySQL)
• Proficiency in Python and data processing libraries (Pandas, NumPy)
• Experience with ETL tools and frameworks (Airflow, Informatica, Talend, etc.)
• Hands-on experience with big data technologies (Hadoop, Spark, Kafka)
• Knowledge of data warehousing concepts and technologies (Snowflake, Redshift, BigQuery)
• Experience with cloud platforms (AWS, Azure, or GCP) and their data services
• Understanding of data modeling techniques and best practices
• Experience with version control systems (Git) and CI/CD pipelines
• Strong problem-solving skills and attention to detail

Advantages

• Experience with real-time data processing and streaming architectures
• Knowledge of data visualization tools (Tableau, Power BI, Looker)
• Experience with NoSQL databases (MongoDB, Cassandra, Redis)
• Background in implementing data lakes and data mesh architectures
• Knowledge of ML/AI data pipelines and feature engineering
• Experience with infrastructure as code (Terraform, CloudFormation)
• Containerization and orchestration experience (Docker, Kubernetes)
• Experience with graph databases
• Open-source contributions to data engineering projects

Soft Skills

• Excellent communication and ability to explain complex technical concepts to non-technical stakeholders
• Strong collaboration skills for cross-functional teamwork
• Self-motivated with ability to work independently in a remote environment
• Analytical thinking and methodical approach to problem-solving
• Adaptability and eagerness to learn new technologies
• Proactive attitude toward identifying and addressing data issues

We Offer

• Competitive salary (based on experience and skills)
• Modern tech stack and opportunity to work with cutting-edge data technologies
• Clear career progression path
• Additional paid time off
• Regular virtual team-building activities
• Opportunity to work on challenging data projects across various industries

If you're passionate about building robust data systems and want to join a team that values innovation and engineering excellence, we'd love to hear from you. Please submit your resume with relevant experience and projects for consideration.

About Us:

Time2Mobile is a tech-driven team focused on building flexible digital solutions for fintech, e-commerce, logistics, and beyond. We work with data at every stage — from collection to analytics — developing robust infrastructures that power smart, data-driven decisions.

We're currently looking for a Middle Data Engineer to join our team and help build and scale our data systems and pipelines.

Your Responsibilities:

• Design, develop, and maintain ETL/ELT data pipelines
• Work with cloud data platforms (AWS, GCP, or Azure)
• Build and maintain data warehouse/lakehouse solutions
• Collaborate closely with data analysts, data scientists, and backend engineers
• Ensure data quality, implement monitoring and logging
• Participate in architectural and technical decision-making

What We Expect:

• 2+ years of experience as a Data Engineer
• Strong knowledge of databases (SQL, PostgreSQL, BigQuery, etc.)
• Hands-on experience with orchestration tools (Airflow, Prefect, or similar)
• Proficiency in Python for data-related tasks
• Understanding of data warehouse/lakehouse architectures
• Familiarity with scalable data infrastructure best practices
• CI/CD experience is a plus
• English level: Intermediate or higher (for documentation and internal communication)

What We Offer:

• Fully remote position
• Flexible working hours
• Paid vacation
• Professional growth and development opportunities
• Projects involving modern tools and data stacks
• A supportive and skilled team environment

Description

GlobalLogic is partnering with a US-based digital health company, whose mission is to connect people in social interactions for health conversations, build online health communities to support each other, and share knowledge about how to deal with the disease

About the client:

Our Client is a fast-paced digital healthcare company that creates a growing portfolio of online health communities for people with chronic conditions. The company’s mission is to improve patients’ quality of life by connecting them with each other, with caregivers, and healthcare industry partners, building beneficial social interactions and meaningful health conversations. 

About the project:
The core of the project is working with the data; the target is to redesign and enhance data-driven solutions. The team is responsible for expanding and optimizing the data flow and data pipeline architecture, modeling and analyzing data, interpreting trends or patterns in complex data sets, and translating them into product and marketing insights. If you are excited by the prospect of optimizing or even re-designing our data architecture to support our next generation of products and data initiatives, we would be thrilled to have you apply!

Requirements

● Strong Python skills

● Strong communication skills

● Strong working SQL knowledge and experience working with relational databases, query authoring (SQL), as well as working familiarity with a variety of databases

● A successful history of manipulating, processing, and extracting value from large disconnected datasets

● Experience building and optimizing data pipelines, architectures, and data sets

● Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement

● Strong analytic skills related to working with unstructured datasets

Technologies:

• Python
• AWS: SES, RDS (MySQL), EC2, ECS, VPC, etc
• Snowflake
• Docker
• dbt
• Airflow

Job Responsibilities

● Manage and optimize core data infrastructure

● Develop a custom data infrastructure not available off-the-shelf

● Build monitoring infrastructure to give visibility into the pipeline’s status

● Monitor all jobs for impact on cluster performance

● Run maintenance routines regularly

● Tune table schemas to minimize costs and maximize performance

● Building and maintaining custom ingestion pipelines

● Build non-SQL transformation pipelines

● Build processes supporting data transformation, data structures, metadata, dependency, and workload management

Who we are

Big Sister AI is building the Sales Score standard — an objective 0-100 rating of sales execution quality. Think Moneyball for sales. Austin-based, Capital Factory portfolio, backed by AWS and Microsoft for Startups.
 

Why this role exists

We're migrating our entire data and audio pipeline to AWS — replacing our current toolstack with a production-grade, multi-tenant architecture. You'll own this build end-to-end.
 

What you'll own

• Design and build cloud-native data and audio processing pipelines on AWS
• Integrate Azure AI services for transcription and LLM scoring
• Own data layer architecture — reliability, schema design, cost optimization
• Build and maintain third-party connector integrations (CRM, notetakers)
• Actively use AI coding tools (Claude, Cursor, Copilot) — hard requirement, not nice-to-have
   

What you need

• Strong AWS hands-on: Lambda, S3, EventBridge, API Gateway, DynamoDB, Secrets Manager
• Azure experience: OpenAI endpoints, Speech Services, Function Apps
• Python 3 — serverless functions, adapters, webhook handlers
• PostgreSQL + SQL — solid data modeling fundamentals
• ELT experience with Data Clouds — Snowflake preferred, BigQuery or Redshift acceptable
• dbt — data modeling and transformation pipelines, production experience required
• Multi-cloud exposure: AWS primary, GCP (BigQuery) and Azure interaction expected
• Self-sufficient — delivers projects with minimal supervision, owns outcomes not just tasks
• Proactive AI tool user — you use Claude/Cursor daily, not occasionally
• Upper-intermediate English — async written communication with US team
• Ukrainian-based — Kyiv/Lviv timezone preferred
   

Nice to have

• AppFlow, Glue, Athena
• OAuth/credential management tools
• Experience working with US-based or distributed teams
   

What we offer

• Competitive Ukrainian market salary
• Direct collaboration with the CEO and US-based advisors
• Greenfield build — you're not inheriting legacy, you're replacing it
• Equity conversation after 3-month trial

EST working hours!!!

CrunchCode — міжнародна сервісна ІТ-компанія з досвідом близько 7 років у розробці вебсервісів і вебзастосунків. Ми працюємо у форматах staff augmentation (outstaff) та outsourcing і підключаємо спеціалістів до проєктів клієнтів у довгостроковій моделі співпраці.

Ми працюємо переважно з проєктами в доменах логістики (включно з last mile),e-commerce, fintech та банкінгу, а також enterprise-рішеннями.
Для нас важливо, щоб проєкт був “чистим” і зрозумілим з точки зору етики та цінності для користувачів.

Ми принципово не беремо проєкти, пов’язані з:
● gambling / гемблінгом,
● adult-контентом та порнографією,
● шахрайством або будь-якою розробкою, що спрямована на обман чи маніпуляції.

What We Offer:
● Fully remote work
● Long-term, stable project
● High level of autonomy and trust
● Minimal bureaucracy
● Direct impact on business-critical logistics systems
● Long-term engagement, not a short-term contract.

Required:
Senior Software / Data Engineer, English B2+
Full-time, EST working hours

Tech Stack:
Python 3.10.x, PySpark, Airflow, Pandas, AWS (ECS, Lambda, SQS, SNS,
ElastiCache, CloudWatch), Delta Lake, Databricks, MySQL (Aurora),
Terraform, Datadog, pytest.
 

Team:
ML Data Engineering — 9 members
2-week sprints: kickoff Monday evenings / demo Friday evenings (EST)

Requirements (Must-have):
- 7+ years of professional software engineering experience.
- Strong proficiency in Python (3.10.x).
- Expertise in large-scale event-driven and distributed system design.
- Strong AWS experience: ECS, Lambda, SQS, SNS, CloudWatch.
- Experience with data processing frameworks: Spark, Databricks.
- Hands-on experience with infrastructure-as-code (Terraform).
- Solid understanding of system performance, profiling, and optimization.
- Experience leading technical projects and mentoring engineers.
- Experience building and maintaining data-intensive backend systems or pipelines.

Responsibilities:
- Lead design and delivery of event-driven, distributed systems for large-scale
 metadata extraction, enrichment, and processing.
- Build and maintain scalable APIs and backend services for high-throughput
 content pipelines on AWS.
- Partner with Data Science, ML Engineering, Infrastructure, and Product teams
 to architect reliable, high-performance systems.
- Provide technical leadership and mentorship across the engineering org.
- Leverage AWS (ECS, Lambda, SQS, SNS, ElastiCache, CloudWatch) to deploy
 resilient production systems.
- Optimize existing systems for scalability, reliability, and performance.
- Ensure system health via monitoring, observability, and automated testing.
- Contribute to engineering strategy — identify gaps, propose initiatives,
 improve existing frameworks.

Nice to Have:
- Experience with Scala or Ruby.
- Experience with Airflow or similar workflow orchestration tools.
- Experience integrating ML or LLM-based models into production systems.
- Bachelor's degree in Computer Science or equivalent.

Hiring Process:
- Intro call
- Technical discussion
- Offer
Start: ASAP

About the Role

We are looking for a Data Engineer to design and implement scalable data pipelines that support Generative AI applications. You will work with large-scale datasets, optimize performance, and ensure seamless data integration across AI workflows.

Responsibilities:

• Design and develop scalable data pipelines to support AI/ML models.
• Work with structured and unstructured data for training and inference.
• Optimize ETL workflows for real-time and batch processing.
• Ensure data quality, governance, and security in cloud environments.
• Collaborate with AI/ML engineers to streamline data workflows.

• Deploy and manage data infrastructure on AWS, GCP, or Azure.

   

Requirements:

• 4+ years of experience in Data Engineering and Big Data technologies.
• Expertise in ETL pipelines, data warehousing, and distributed computing.
• Strong knowledge of SQL, NoSQL, and data lakes.
• Experience with cloud-based data services (AWS Glue, BigQuery, Azure Data Factory).
• Proficiency in Python, Spark, Kafka, Airflow.
• Experience with CI/CD, DevOps, and Agile methodologies.

What You’ll Get at Uvik:

• Generous paid time off: 18 vacation days + 12 sick leaves annually.
• Flexibility: manage your schedule, work fully remote, and keep a healthy work-life balance.
• Challenging projects: work with global clients and the latest technologies.
• Growth opportunities: we invest in your development and support career advancement.
• Competitive salary in a fast-growing international company.

Snowflake Data Engineer — Remote (GMT +1-5)

📍 Remote | 🕐 One interview. That's it.

WHO WE ARE

SouthRivers Data, we're an engineering-led company - built by engineers, run by engineers. That means no explaining why tech debt matters, no translating "we need refactoring time" into business speak, and no decisions made by people who've never written a line of code. We get it, because we've been there.

We believe that a great engineer is defined by two things equally: technical mastery and the ability to work with people. One without the other isn't enough for us - and probably isn't enough for you either.

THE ROLE

We're looking for a Databricks Data Engineer to join our project and work on data-intensive client projects - think Data Lakehouses implementation , modernization, pipeline engineering or migrations.

You'll be engaged on a project basis, with clear scope and a team that actually understands your work.

WHAT WE EXPECT

Required:

• Strong SQL and Python - you write clean, production-grade code
• Experience with Databricks and Apache Spark - you know how it works under the hood and have solid experience
• Workflow orchestration with Airflow, Dagster, or equivalent
• Solid understanding of Data Engineering principles, Data Modelling, dimensional design, and best practices
• Experience with DWH, Medallion and Lakehouse architectures — you've designed or maintained one, not just heard the term
• Experience with one of the cloud provides AWS\Azure\GCP

Nice to Have:

• dbt
• Snowflake
• CI\CD

THE PROCESS

One 1-hour interview with us. Possibly one short call with the client. That's the entire process - we respect your time and we've structured things so we can make a decision fast.

No take-home assignments.

THE SETUP

• Fully remote - work from wherever you are
• Contract / B2B engagement
• 2–4 week onboarding notice window

If you've been burned by companies that talk about engineering culture but are run by spreadsheets - this is the alternative.

Snowflake Data Engineer — Remote (GMT +1-5)

📍 Remote | 🕐 One interview. That's it.

WHO WE ARE

SouthRivers Data, we're an engineering-led company - built by engineers, run by engineers. That means no explaining why tech debt matters, no translating "we need refactoring time" into business speak, and no decisions made by people who've never written a line of code. We get it, because we've been there.

We believe that a great engineer is defined by two things equally: technical mastery and the ability to work with people. One without the other isn't enough for us - and probably isn't enough for you either.

THE ROLE

We're looking for a Snowflake Data Engineer to join our project and work on data-intensive client projects - think DWH implementation , modernization, pipeline engineering or migrations.

You'll be engaged on a project basis, with clear scope and a team that actually understands your work.

WHAT WE EXPECT

Required:

• Strong SQL and Python - you write clean, production-grade code
• Experience with Snowflake - you know how it works under the hood and query optimization
• Workflow orchestration with Airflow, Dagster, or equivalent
• Solid understanding of Data Engineering principles, Data Modelling, dimensional design, and best practices
• Experience with DWH architectures — you've designed or maintained one, not just heard the term

Nice to Have:

• dbt
• Data Vault knowledge\experience

THE PROCESS

One 1-hour interview with us. Possibly one short call with the client. That's the entire process - we respect your time and we've structured things so we can make a decision fast.

No take-home assignments.

THE SETUP

• Fully remote - work from wherever you are
• Contract / B2B engagement
• 2–4 week onboarding notice window

If you've been burned by companies that talk about engineering culture but are run by spreadsheets - this is the alternative.