Jobs Data Engineer

We’re looking for a Senior Data Architect with strong hands-on Azure experience to design and own a complex cloud data platform.

This is not a standard Data Engineer role — we need someone who has personally designed data architectures, made architecture decisions, and owned solutions from design through implementation.

What you’ll do

• Design and own data platform architecture on Azure
• Build scalable solutions using Azure + Databricks
• Design Lakehouse / Data Warehouse architectures
• Define data models, ETL/ELT flows, and data pipelines
• Work with structured and unstructured data from multiple sources and file formats
• Define data governance, security, access control, and data quality standards
• Work closely with Data Engineers, analytics teams, and business stakeholders
• Drive architecture decisions and support implementation

What we’re looking for

• Proven experience as a Data Architect
• 4+ years of hands-on Azure experience, including recent projects
• Strong Databricks experience
• Strong experience with Azure Data Platform
• Azure Data Lake / ADLS
• Azure Data Factory
• Azure Synapse
• Strong Python + SQL
• ETL/ELT and cloud data pipelines
• Data Warehousing and dimensional modeling
• Data governance and security
• Experience designing complex data architectures with unstructured data and different file formats
• English — strong conversational level, ideally C1

Important

We need someone with real architecture ownership, not only Data Engineering experience.

Your CV should clearly show what Azure data platforms you personally designed and owned, which architecture decisions you made, and how you worked with Azure and Databricks.

Location

Remote, working in the CET time zone.

Candidates should currently be located in the EU, Serbia, Albania, Bosnia and Herzegovina, Kosovo, Montenegro, North Macedonia, Armenia, Georgia, Azerbaijan, or Moldova.

Ukrainian and CIS candidates who have relocated to an eligible country are welcome.

Current location in Ukraine, Russia, Belarus, or Turkey cannot be considered for this project.

We are a product company building AI-powered mobile applications used by over 10 million people in 150 countries. We own the entire product lifecycle — from the initial idea to large-scale global implementation. We thrive in a fast-paced environment, making data-driven decisions without unnecessary bureaucracy. If you value autonomy, rapid releases, and seeing the direct impact of your work, you will fit right in.
 

The Role

We are looking for a Senior DevOps Engineer to take full ownership and leadership of the infrastructure for our ambitious project in the Cloud Gaming & Streaming space.

In this role, you will architect, scale, and maintain a high-performance, fault-tolerant system provisioning and streaming content across a server fleet growing from hundreds toward thousands of machines. You will lead infrastructure decisions, set technical standards, build key systems (like observability and bare-metal orchestration) from scratch, and mentor a Mid DevOps Engineer on the team.
 

Work Format & Relocation

• Location: Dubai, UAE (Office).
• Trial Period: First 2–3 months are fully remote for a smooth onboarding.
• Relocation Support: Full corporate visa sponsorship and relocation package provided after the trial period.
   

Key Responsibilities

• Fleet Architecture & Provisioning: Architect and automate end-to-end bare-metal and virtualized host provisioning — storage, GPU passthrough (vfio), and VM lifecycle across a large, heterogeneous server fleet.
• Orchestration & Scale: Design and maintain fleet-scale orchestration systems: parallel deployments, health checks, and self-healing routines ensuring consistency across thousands of machines.
• Infrastructure as Code & Configuration: Lead IaC practices using Terraform and Ansible to maintain reproducible host configurations, deterministic automation, and VM images.
• Advanced Virtualization & OS Administration: Deeply manage Linux/KVM virtualization (libvirt, QEMU) and Windows guest systems, including complex GPU passthrough and low-latency virtual networking.
• Greenfield Observability: Architect and implement the observability stack from scratch (Prometheus, Grafana, Loki/ELK) across the entire fleet for deep performance monitoring and alerting.
• Network & Traffic Management: Design and optimize network configurations at scale — NAT, port forwarding, routing, and traffic paths for thousands of concurrent, low-latency streaming clients.
• CI/CD & Deterministic Automation: Build robust CI/CD pipelines (GitLab CI / GitHub Actions) for infrastructure code, images, and deterministic scripting (Bash, Python, PowerShell).
• Security & Storage: Implement enterprise-grade secrets management (Vault / SOPS) and manage large-scale content distribution via S3-compatible object storage (e.g., Cloudflare R2).
• Leadership & Incident Response: Set reliability engineering standards, drive incident response/on-call processes, and collaborate closely with core C++/C# infrastructure engineers.
   

Requirements

• Experience: 4+ years in a DevOps / Infrastructure role with proven experience building and managing large-scale, high-load systems or large server fleets (dozens/hundreds+ of nodes).
• OS & Virtualization Expertise: Deep administration skills in both Linux and Windows; practical expertise with KVM/libvirt, QEMU, and GPU passthrough / vfio.
• IaC & Configuration Management: Strong hands-on experience with Terraform and Ansible for host consistency, image management, and fleet-wide automation.
• Scripting Mastery: High proficiency in Python, Bash, or PowerShell with the ability to write deterministic, idempotent, and restart-safe automation scripts across heterogeneous hardware.
• Networking & Observability: Strong grasp of Linux networking (NAT, iptables, routing, traffic shaping) and experience standing up monitoring/logging stacks (Prometheus, Grafana, Loki/ELK) from scratch.
• CI/CD & Security: Experience automating infrastructure via GitLab CI/GitHub Actions and managing secrets at scale (Vault, SOPS).
• Language: English (Upper-Intermediate / B2 or higher — required for technical collaboration).
   

Nice-to-have

• Direct experience in Cloud Gaming, real-time data streaming, or high-load gaming environments.
• Hands-on experience with GPU-heavy workloads and large-file distribution via object storage (S3 / Cloudflare R2).
• Basic knowledge of C++ or C# to collaborate effectively with core streaming infrastructure developers.
   

What We Offer

• Architectural Greenfield & Autonomy: Full ownership to design the fleet observability, orchestration, and automation architecture from zero.
• Leadership & Real Impact: Direct influence on the tech stack of a Cloud Gaming platform targeting a global, multi-million user audience.
• Relocation Package: Full financial and organizational support for your move to Dubai (corporate visa, flight tickets, initial housing) after the trial period.
• Modern Office: Work from a vibrant, tech-driven workspace in Dubai alongside a strong engineering team.
• Fast-Paced Culture: A product-driven environment with quick decision-making, high engineering freedom, and zero bureaucracy.
• Compensation: Highly competitive USD-pegged salary matching your senior technical background.

PwC is a global network of more than 370,000 professionals in 149 countries that turns challenges into opportunities. We create innovative solutions in audit, consulting, tax and technology, combining knowledge from all over the world.

PwC SDC Lviv, opened in 2018, is part of this global space. It is a place where technology is combined with team spirit, and ambitious ideas find their embodiment in real projects for Central and Eastern Europe.

What do we guarantee?

• Work format: Remote or in a comfortable office in Lviv - you choose.
• Development: Personal development plan, mentoring, English and Polish language courses.
• Stability: Official employment from day one, annual review of salary and career prospects.
• Corporate culture: Events that unite the team and a space where everyone can be themselves.

PwC Cloud & Digital team supports global cloud projects across Cloud Strategy, Migrations, Data Analytics, and DevOps. We help clients adopt cloud infrastructure, modernize data platforms, and optimize operations.

Your future role:

• Building data platforms (data warehouses, lakes, lakehouses) using Azure Databricks, MS Fabric, Azure Data Factory.
• Designing data flows using medallion architecture and supporting data migrations from legacy systems.
• Conducting data assessments with Data Modelers/Analysts and addressing data quality issues.
• Working with senior stakeholders to gather requirements and support modern data architecture design.
• Supporting Data Governance activities, especially around MDM and Data Quality.
• Understanding Data Science/Analytics use cases in industries like Consumer Goods, Retail, Manufacturing, or Financial Services.

Apply if you have:

• 4+ years of experience in Data Engineering or related fields (BI, Data Science).
• Hands‑on experience with Databricks, Snowflake, BigQuery, MS Fabric.
• Experience building data warehouses/lakehouses with Azure Data Factory / Synapse.
• Skills in PySpark/Python and SQL.
• Some exposure to CI/CD (Azure DevOps, Jira).
• B2+ English and ability to prepare technical documentation.
• Experience using modern tech and AI tools in daily work.

Nice to have:

• Cloud certifications (Azure/AWS/GCP) and Data Governance certifications.
• Training via platforms like Coursera/Udemy/Datacamp.
• Knowledge of data modelling (e.g., Kimball), Data Strategy, Data Quality, and MDM.
• Experience with Agile (Scrum), ML/GenAI use cases, or Agentic AI for data automation.
• Work with senior stakeholders (e.g., CDOs) in Manufacturing, Consumer Goods, or Financial Services.

Policy statements:
https://www.pwc.com/ua/uk/about/privacy.html

We are looking for a Trainee Big Data Engineer who is interested in starting a career in Data Engineering.

You will join an experienced data engineering team and have the opportunity to learn how data is collected, processed, transformed, and prepared for analytics. You will work with Python, SQL, and modern Big Data technologies while receiving guidance and support from experienced engineers.

Commercial experience is not required - we are happy to consider candidates with knowledge gained through university studies, courses, internships, or personal projects. This is a great opportunity to gain practical experience with real-world data and learn how modern data engineering solutions are built.

Responsibilities:

• Assist with building and maintaining data pipelines.
• Work with data from different sources.
• Help clean and transform data.
• Write basic SQL queries.
• Use Python for data processing.
• Participate in data quality checks and troubleshooting.
• Learn and work with Big Data technologies such as PySpark / Apache Spark.
• Collaborate with experienced Data Engineers and Data Analysts.
• Learn and apply best practices in data engineering.

Requirements:

• Basic knowledge of Python.
• Basic knowledge of SQL.
• Basic understanding of relational databases.
• Understanding of basic data processing and ETL/ELT concepts.
• Familiarity with data structures and algorithms.
• Basic understanding of cloud computing.
• Strong interest in Data Engineering and Big Data.
• English — Upper-Intermediate (B2) or higher.

Would Be a Plus:

• Basic knowledge of PySpark / Apache Spark.
• Familiarity with Palantir Foundry or Databricks.
• Understanding of data warehouses or data lakes.
• Basic knowledge of data modeling.
• Experience with Git.
• University degree or ongoing studies in Computer Science, Data Engineering, Mathematics, or a related field.
• Academic, personal, internship, or course projects related to Python or Data Engineering.

Senior Data Engineer
 

We’re a London-based fintech on a mission to help banks and small businesses thrive in a digital-first economy. Founded in 2017, we bring together the energy and flexibility of a high-growth scale-up with the backing of global financial institutions. Our cloud-based platform powers end-to-end merchant services for banks, combining payments and business banking into one seamless experience. We partner with trusted names like NatWest (Tyl by NatWest), NAB (NAB Hive) and Truist (Truist Merchant Engage) in the United States to help their small business customers grow and succeed.
 

We’re a close-knit team of designers, engineers, and financial services experts who care deeply about what we build and how we work together. We value curiosity, collaboration, and making things better every day. Whether you’re technical, creative, or commercial, you’ll find space here to do your best work, develop your skills, and be part of something meaningful. We’re headquartered in London and expanding our team in South Africa – and we’d love for you to be part of the journey.
 

The role
 

As a Senior Backend Engineer in Data, you will own one or more components of our backend microservice applications. You will join the team that builds and maintains the data ingestion pipelines that turn raw banking and transactional data into actionable insights.
 

This is a great opportunity to get full exposure to the entire tech stack involved in building data pipelines for ingestion, data persistence and data APIs powering our micro-frontends at scale. We have a fun environment with a high level of responsibility, autonomy, trust and transparency and work very closely with the product development and business teams.
 

Responsibilities
 

• Design and implement scalable ingestion pipelines that work in both streaming and batch modes.
 

• Integrate with third-party APIs, banks and payment processors to ingest transactional data.
 

• Write production-quality code in Java 21 (Spring Boot) to develop microservices and data integration endpoints.
 

• Use reactive frameworks (Spring WebFlux) where needed for asynchronous processing.
 

• Operate and optimise Kafka-based streaming workflows and event-driven architectures.
 

• Implement large-scale data processing jobs on Azure Databricks with Spark (Scala/Python) to transform and aggregate data. Optimise Spark jobs for performance and cost efficiency on Azure.
 

• Design and maintain schemas in MS SQL Server and ensure data models are efficient for queries and analytics.
 

• Ensure data quality and governance: validation, schema evolution, lineage and monitoring.
 

• Expose data via APIs and data products consumed by micro-frontends and reporting tools.
 

• Embed pre-built data science solutions into the data estate.
 

• Provide Level 3 support for production issues.
 

• Collaborate closely with product, engineering and business teams to translate requirements into production-ready pipelines.
 

What we are looking for
 

• Expert in Java 21+ with Spring and Spring Boot.
 

• Hands-on experience with messaging and streaming platforms. Apache Kafka (or equivalent) experience is required – our pipelines ingest high-volume events in real time. Knowledge of Azure Event Hubs (Kafka-compatible) is also acceptable.
 

• Proficient in T-SQL with experience on MS SQL Server.
 

• Good software design and coding practices. Familiar with unit/integration testing (JUnit, Cucumber), version control (Git), and agile methodologies.
 

• Strong problem-solving, communication, and teamwork. Able to translate complex data requirements into reliable technical solutions.
 

• Eager to learn new big data and cloud technologies and keep your skills up to date.
 

• Enthusiastic about finding creative ways to solve problems and curios to explore new areas.
 

Nice-to-Have Skills
 

• Experience with big data on Microsoft Azure. Comfortable using Azure Databricks/Spark, and Azure storage (Blob/SQL/Cosmos).
 

• Exposure to Scala or Python is a plus for Spark jobs.
 

• Experience with Spring WebFlux (reactive programming) is highly desirable.
 

• Ability to containerize applications (Docker) and deploy/manage them in Kubernetes clusters.
 

• Familiar with NoSQL/database technologies; we use Cosmos DB for scalable, multi-region data.
 

• Experience with Terraform or similar tools to provision cloud resources. Familiar with CI/CD practices (we use GitOps/ArgoCD pipelines).
 

• Exposure to logging/monitoring stacks (ELK/Elastic, Prometheus/Grafana) and performance testing tools (K6, JMeter).
 

• Interest or experience in emerging AI/ML tools and LLMs (e.g. Ollama LLM) as the company explores intelligent analytics.
 

Who we are looking for
 

• Ideally someone who has worked for a Fintech start-up.
 

• Starter-finisher attitude to manage work.
 

• Strong verbal and written English communication skills.
 

• Comfortable working outside of rigid structures and frameworks.
 

• Effective working in ambiguous environments.
 

• You are a team player and can work cross-team - for instance with business-minded staff, designers, product owners, and everything in between.
 

• Actively mentors and supports others, sharing knowledge, guiding junior engineers, and contributing to a strong engineering culture.
 

• Builds alignment and influence, fostering trusted relationships and helping teams make better technical and product decisions.
 

What we stand for
 

• We believe we are better together when we listen, engage and support each other, we want you to bring your expertise and experience to work every day.
 

• We are passionate about what we are doing and want you to share this with us, enjoy your time with us, stay calm under pressure and bring positive energy to the team.
 

• We are all on a journey together, we want your ambition and flexible mind set to embrace the twists and turns as we grow as a business.
 

Your wellbeing and professional growth is important to us. If you join Pollinate, you can expect:
 

• Access to career coaching, life coaching and therapy from our employee experience partners Plumm.
 

• Access to Pluralsight for Engineering roles or a Growth Budget to develop your learning.
 

• Flexible hybrid working where our hub is used for team or collaboration meetings and company get togethers.
 

As part of Pollinate, you’ll be working with experts across payments, technology, customer experience, and financial services, supported by a world-class network of partners. Join us to be a key part of a team that’s changing the future of payments, with the freedom to make your mark. Together, we’ll push the boundaries of what’s possible with payment enabled merchant services for SMB’s around the world.
 

This Job Description covers the main areas of your responsibilities - it is not an exhaustive list.
 

About the Role:

We are looking for an experienced Senior Data Engineer to join our team and help build scalable, secure, and high-performance data platforms. In this role, you will work closely with Data Architects, Engineers, Analysts, DevOps specialists, and Data Scientists to design, develop, and optimize modern cloud-based data ecosystems.

This is a full-time remote position for a senior-level professional who can commit 40 hours per week and take ownership of complex data engineering initiatives.

Responsibilities:

As a Senior Data Engineer, you will:

* Collaborate with Data Architects on designing and implementing data solutions across Azure, AWS, or IBM Cloud environments

* Build, maintain, and optimize modern data ecosystems and data pipelines

* Develop and support data ingestion, transformation, and processing solutions

* Work closely with cross-functional teams, including Data Engineers, Analysts, DevOps Engineers, and Data Scientists

* Implement security best practices to ensure the reliability and protection of cloud infrastructure and data processes

* Apply modern engineering principles and methodologies to support business growth and innovation

* Identify opportunities to improve data quality, reliability, scalability, efficiency, and overall platform performance

* Optimize data solutions to balance performance, maintainability, and cost-effectiveness

* Design and execute unit, system, and integration testing strategies

* Contribute to continuous improvement initiatives and engineering best practices

Requirements:

* Strong commercial experience as a Data Engineer

* Advanced proficiency in Python for data processing, transformation, and analysis

* Strong expertise in SQL, including query optimization and database performance tuning

* Hands-on experience with Azure and/or AWS data platforms and services

* Experience designing and maintaining scalable cloud-based data solutions

* Solid understanding of data engineering best practices, data modeling, and ETL/ELT processes

* Experience with software development lifecycle methodologies and Agile environments

Nice to Have:

* Experience with IBM Cloud data services

* Knowledge of data governance and cloud security practices

* Experience working in enterprise-scale data environments

What We Offer:

-Paid vacation and sick leave

-We provide the equipment you need to work comfortably (if required)

-We cover 50% of courses if you want to grow professionally

-Regular salary reviews based on your performance

-Competitive salary, depending on your experience

-Always on-time payments — no delays

-A normal, supportive team without unnecessary bureaucracy

ZentixSoft is looking for a Senior AWS Cloud Data Engineer (Financial Ecosystems) ☁️📊

We are significantly expanding our data engineering and analytics direction for our strategic international partners and are looking for a highly mature Senior Data Engineer to drive cloud-native banking data products.
 

Note: This is an Outstaffing role where you will join a high-impact core data team. 

⚠️ A Quick Note for Applicants: To move forward swiftly, your CV must clearly highlight your hands-on architecture decisions, specific AWS technologies used, data volumes, and the precise banking data products you have delivered.

💡 Why ZentixSoft? 
💸 Salary Review: A structured system of compensation reviews aligned with your expertise and engineering growth. 
🦾 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.
 

If you are ready to architect resilient data solutions for a massive financial ecosystem, here is what our perfect match looks like:

1️⃣ Engineering Seniority: A proven track record of designing, building, and operating large-scale data platforms specifically within the AWS cloud environment. 
2️⃣ FinTech & Banking Domain: Solid experience handling sensitive financial data products (focused on areas like Risk, Compliance, Fraud Prevention, Finance, or Regulatory Reporting). 
3️⃣ Governance Mastery: Deep understanding of banking infrastructure needs, including strict data lineage, quality validation, auditability, and data security. 
4️⃣ Independence: Ability to make standalone architectural and technical design choices, turning raw business requirements into robust, high-volume production pipelines. 
5️⃣ Communication: Fluent English combined with strong stakeholder management skills to align easily with business, tech, and compliance teams.
 

Project Details: 
📍 Location: Primarily remote, with a preference for candidates located in the Baltics (or other EU countries). 
✈️ Work Model: Occasional onsite visits to client offices in the Baltics (approx. once per month for 2–3 days). 
⏳ Duration: Long-term cooperation. 
🚀 Start: ASAP.

About the Client:

Our client is a leading enterprise data platform company building an open, high-performance data lakehouse for AI and analytical workloads. The platform combines an intelligent SQL query engine, an AI-ready semantic layer, and an open catalog built on Apache Iceberg — enabling Fortune 500 companies across finance, energy, manufacturing, and logistics to unify, query, and govern data at massive scale across cloud and on-premise sources.

About the Role:

We are looking for a Middle-level Software Engineer to work on the core query engine of a large-scale distributed data platform. You will develop features across query planning, optimization, and execution, contribute to performance-critical components, and help evolve the platform's ability to process massive analytical workloads across heterogeneous data sources.

This is a systems-level, backend engineering role focused on distributed data processing internals — not application development or CRUD services.

Responsibilities:

• Develop and maintain features across the query engine — planning, optimization, execution, and data access layers.
• Write high-quality, performance-conscious code in Java and/or C++.
• Work with SQL semantics, query plans, and execution operators over large-scale distributed data.
• Integrate with columnar formats, open table formats, and connectivity drivers used across the platform.
• Contribute to CI/CD pipelines and automated testing — participate in build, test, and release workflows in Jenkins.
• Deploy and validate work in Kubernetes (GKE / EKS / AKS) across GCP, AWS, and Azure using Docker.
• Debug complex issues spanning query planning, distributed execution, memory management, and I/O.
• Collaborate closely with US-based engineering teams on design reviews, code reviews, and technical decisions.

Required Qualifications:

• Education: B.S. or M.S. in Computer Science, Computer Engineering, or a related technical field.
• Programming: Strong proficiency in Java or C++, with solid OOP and software design fundamentals. Candidates comfortable with both are especially valued.
• SQL & Data: Strong SQL skills and solid understanding of relational and analytical data systems, including query execution concepts.
• Data processing systems experience: Hands-on experience with data processing systems — query engines, distributed databases, ETL/ELT frameworks, or analytical platforms.
• Engineering experience: 3+ years in backend/systems software engineering.
• CI/CD & DevOps basics: Practical experience with Jenkins pipelines and modern development workflows.
• Containers: Working knowledge of Docker and basic Kubernetes (running workloads, debugging pods, kubectl fluency).
• Cloud: Comfortable operating in at least one major cloud (GCP, AWS, or Azure).
• Version Control: Confident with Git / GitHub workflows.
• English: Upper-Intermediate or higher (B2+) — daily written and verbal communication with a US-based engineering team.
• Availability: Able to work EU hours with a 2–3 hour shift toward US West Coast time to ensure daily overlap with the client team.

Desired Skills:

• Experience with Apache Arrow (columnar in-memory format).
• Familiarity with Apache Calcite (SQL parsing, planning, optimization framework).
• Exposure to Gandiva or LLVM-based expression compilation.
• Experience with open table formats — Apache Iceberg, Delta Lake, or Hudi.
• Familiarity with distributed computing frameworks (e.g., Apache Spark, Kafka) and MPP SQL query engines (e.g., Presto, Trino, or similar).
• Understanding of query planning, optimization, and execution internals.
• Experience with data connectivity drivers: JDBC, ODBC, Arrow Flight.
• Kubernetes on managed services (GKE / EKS / AKS) and multi-cloud exposure.
• IaC tools such as Terraform.
• Experience with performance profiling and optimization of latency-sensitive systems.

Join an exciting journey to create a cutting-edge Consumer Data Lake for a leading global organization based in Europe. This platform will unify, process, and leverage consumer data from various systems, unlocking advanced analytics, insights, and personalization opportunities. As a Senior Data Engineer, you will play a pivotal role in shaping and implementing the platform's architecture, focusing on hands-on technical execution and collaboration with cross-functional teams.

Your work will transform consumer data into actionable insights and personalization on a global scale. Using advanced tools to tackle complex challenges, you’ll innovate within a collaborative environment alongside skilled architects, engineers, and leaders.

Key Responsibilities:

• Hands-On Development: Build, maintain, and optimize data pipelines for ingestion, transformation, and activation.
• Create and implement scalable solutions to handle diverse data sources and high volumes of information
• Data Modeling & Warehousing: Design and maintain efficient data models and schemas for a cloud-based data platform.
• Develop pipelines to ensure data accuracy, integrity, and accessibility for downstream analytics.
• Collaboration: Partner with Solution Architects to translate high-level designs into detailed implementation plans.
• Work closely with Technical Product Owners to align data solutions with business needs.
• Collaborate with global teams to integrate data from diverse platforms, ensuring scalability, security, and accuracy.
• Platform Development: Enable data readiness for advanced analytics, reporting, and segmentation.
• Implement robust frameworks to monitor data quality, accuracy, and performance.
• Testing & Quality Assurance: Implement robust security measures to protect sensitive consumer data at every stage of the pipeline
• Ensure compliance with data privacy regulations (e.g., GDPR, CCPA ..) and internal policies.
• Monitor and address potential vulnerabilities, ensuring the platform adheres to security best practices.

Requirements:

• Over 4+ years of experience showcasing technical expertise and critical thinking in data engineering.
• Hands-on experience with DBT and strong Python programming skills.
• Proficiency in Snowflake and expertise in data modeling are essential.
• Demonstrated experience in building consumer data lakes and developing consumer analytics capabilities is required.
• In-depth understanding of privacy and security engineering within Snowflake, including concepts like RBAC, dynamic/tag-based data masking, row-level security/access policies, and secure views.
• Ability to design, implement, and promote advanced solution patterns and standards for solving complex challenges.
• Familiarity with multiple cloud platforms (Azure or GCP preferred, with a focus on Azure).
• Practical experience with Big Data batch and streaming tools.
• Competence in SQL, NoSQL, relational database design (SAP HANA experience is a bonus), and efficient methods for data retrieval and preparation at scale.
• Proven ability to collect and process raw data at scale, including scripting, web scraping, API integration, and SQL querying.
• Experience working in global environments and collaborating with virtual teams.
• A Bachelor’s or Master’s degree in Data Science, Computer Science, Economics, or a related discipline.

We are looking for a Lead Data Engineer to drive the design and implementation of scalable data solutions, pipelines, and analytics-ready datasets. 

What You’ll Do 

• Lead design and implementation of data pipelines, transformations, and curated datasets 
• Translate business requirements into structured data solutions and models 
• Guide and execute development of reusable, analytics-ready data assets 
• Ensure consistency in how key data elements are defined and used across systems 
• Collaborate with stakeholders to define and refine data requirements and logic 
• Review and guide engineering work to ensure quality, performance, and scalability 
• Establish best practices for data engineering, transformation, and data quality 
• Support integration of data across multiple domains and systems 
• Contribute to architecture decisions across data platforms and tooling 
• Mentor and support other engineers on the team 

What You Bring 

Must-Haves 

• 5+ years of experience in data engineering, analytics engineering, or related fields 
• Strong SQL expertise and experience designing complex data transformations 
• Hands-on experience with modern data platforms (e.g., GCP BigQuery, Databricks, Snowflake) 
• Data platforms experience. ELT or ETL, orchestration such as Airflow or dbt, Spark, data warehouses and lakehouses such as Snowflake, BigQuery, or Databricks, streaming such as Kafka or Kinesis, metadata and data quality 
• Proficiency in Python 
• Strong understanding of data modeling concepts and data structuring for analytics 
• Experience working with stakeholders to define requirements and deliver data solutions 
• Ability to balance hands-on delivery with technical guidance 

Nice-to-Haves 

• Familiarity with data governance, lineage, or metadata management concepts 
• Experience working with cross-domain data (e.g., customer, product, transactions) 
• Exposure to financial services or other data-intensive industries 
• Experience supporting migration or evolution of data platforms (e.g., toward Databricks) 
• Experience with orchestration tools (e.g., Airflow, Cloud Composer) 
• Exposure to data modeling concepts (e.g., dimensional models, data marts, reusable datasets) 

What’s in It for You 

• Impact at scale. Help shape enterprise AI, software, and data programs across industries. 
• Growth and mastery. Work with a seasoned team from leading consulting and technology backgrounds. 
• Build real products. Work on production ready assets with autonomy over key technical decisions. 

About the Role:

We are looking for an experienced Senior Data Engineer to join our team and help build scalable, secure, and high-performance data platforms. In this role, you will work closely with Data Architects, Engineers, Analysts, DevOps specialists, and Data Scientists to design, develop, and optimize modern cloud-based data ecosystems.

This is a full-time remote position for a senior-level professional who can commit 40 hours per week and take ownership of complex data engineering initiatives.

🔹 Responsibilities:

As a Senior Data Engineer, you will:

* Collaborate with Data Architects on designing and implementing data solutions across Azure, AWS, or IBM Cloud environments

* Build, maintain, and optimize modern data ecosystems and data pipelines

* Develop and support data ingestion, transformation, and processing solutions

* Work closely with cross-functional teams, including Data Engineers, Analysts, DevOps Engineers, and Data Scientists

* Implement security best practices to ensure the reliability and protection of cloud infrastructure and data processes

* Apply modern engineering principles and methodologies to support business growth and innovation

* Identify opportunities to improve data quality, reliability, scalability, efficiency, and overall platform performance

* Optimize data solutions to balance performance, maintainability, and cost-effectiveness

* Design and execute unit, system, and integration testing strategies

* Contribute to continuous improvement initiatives and engineering best practices

🔹 Requirements:

* Strong commercial experience as a Data Engineer

* Advanced proficiency in Python for data processing, transformation, and analysis

* Strong expertise in SQL, including query optimization and database performance tuning

* Hands-on experience with Azure and/or AWS data platforms and services

* Experience designing and maintaining scalable cloud-based data solutions

* Solid understanding of data engineering best practices, data modeling, and ETL/ELT processes

* Experience with software development lifecycle methodologies and Agile environments

Nice to Have:

* Experience with IBM Cloud data services

* Knowledge of data governance and cloud security practices

* Experience working in enterprise-scale data environments

🌍 What We Offer:

-Paid vacation and sick leave

-We provide the equipment you need to work comfortably (if required)

-We cover 50% of courses if you want to grow professionally

-Regular salary reviews based on your performance

-Competitive salary, depending on your experience

-Always on-time payments — no delays

-A normal, supportive team without unnecessary bureaucracy

🚀 Senior Data Engineer (EU)

About the Role:

We are looking for an experienced Senior Data Engineer to join our team and help build scalable, secure, and high-performance data platforms. In this role, you will work closely with Data Architects, Engineers, Analysts, DevOps specialists, and Data Scientists to design, develop, and optimize modern cloud-based data ecosystems.

This is a full-time remote position for a senior-level professional who can commit 40 hours per week and take ownership of complex data engineering initiatives.

🔹 Responsibilities:

As a Senior Data Engineer, you will:

* Collaborate with Data Architects on designing and implementing data solutions across Azure, AWS, or IBM Cloud environments

* Build, maintain, and optimize modern data ecosystems and data pipelines

* Develop and support data ingestion, transformation, and processing solutions

* Work closely with cross-functional teams, including Data Engineers, Analysts, DevOps Engineers, and Data Scientists

* Implement security best practices to ensure the reliability and protection of cloud infrastructure and data processes

* Apply modern engineering principles and methodologies to support business growth and innovation

* Identify opportunities to improve data quality, reliability, scalability, efficiency, and overall platform performance

* Optimize data solutions to balance performance, maintainability, and cost-effectiveness

* Design and execute unit, system, and integration testing strategies

* Contribute to continuous improvement initiatives and engineering best practices

🔹 Requirements:

* Strong commercial experience as a Data Engineer

* Advanced proficiency in Python for data processing, transformation, and analysis

* Strong expertise in SQL, including query optimization and database performance tuning

* Hands-on experience with Azure and/or AWS data platforms and services

* Experience designing and maintaining scalable cloud-based data solutions

* Solid understanding of data engineering best practices, data modeling, and ETL/ELT processes

* Experience with software development lifecycle methodologies and Agile environments

Nice to Have:

* Experience with IBM Cloud data services

* Knowledge of data governance and cloud security practices

* Experience working in enterprise-scale data environments

🌍 What We Offer:

-Paid vacation and sick leave

-We provide the equipment you need to work comfortably (if required)

-We cover 50% of courses if you want to grow professionally

-Regular salary reviews based on your performance

-Competitive salary, depending on your experience

-Always on-time payments — no delays

-A normal, supportive team without unnecessary bureaucracy

We are looking for a Senior Data Engineer with specialized domain expertise in fraud detection, Anti-Money Laundering (AML), or transaction-monitoring systems to establish data-quality foundations for decision engines.

Our client is a fast-growing European FinTech company in the Business Spend Management space - providing corporate cards and related financial products to SME and mid-sized businesses across the EU and UK in a regulated environment.
You will embed directly into a product squad as a hands-on Individual Contributor (IC). 

Key Responsibilities:

• Architect and build robust data-quality frameworks specifically designed to power decision engines.
• Design, scale, and maintain reliable, high-throughput production data pipelines.
• Build infrastructure and workflows that enable fast, seamless deployment of fraud and transaction-monitoring rules.
• Bring deep domain knowledge in Fraud, AML, and Transaction Monitoring to production data engineering workflows.
• Multiply the output and quality of your squad while sharing data engineering patterns and best practices across the organization.

Requirements:

• Strong, senior-level 5+ years expertise in Python for data engineering and production pipeline development.
• Experience/background in Fraud, AML, or Transaction-Monitoring systems.
• Proven track record of establishing data-quality foundations for automated decisioning systems.
• Extensive experience building production data pipelines and supporting rapid rule deployment workflows.

Nice-to-Have Skills:

• Hands-on experience with Airflow, SQL, PostgreSQL, and Google BigQuery (standard stack for data/analytics workloads).
• Experience working in hybrid cloud environments (AWS primary + GCP analytics).
• Familiarity with modern engineering workflows (Linear, GitHub, Notion, Slack) and AI-assisted development (Claude Code, GitHub Copilot).

Client

Our client is the UK’s leading development finance institution, dedicated to supporting companies in developing countries and driving sustainable growth.

Position overview

We are looking for a Senior/Lead Data Engineer to join a distributed team working on modern cloud-based data solutions within the Azure ecosystem. The role involves designing, developing, and maintaining scalable data pipelines and integrations that support business-critical reporting, analytics, and operational processes.

You will work closely with cross-functional teams, contributing to architecture decisions, delivery processes, and continuous platform improvements while ensuring high standards of quality and reliability.

Responsibilities

• Design, develop, and maintain data pipelines and ETL/ELT processes using Azure technologies
• Build and support scalable solutions using Azure Data Factory (ADF), Azure SQL, and other Azure services
• Develop backend logic and automation using Python, Azure Functions, and Logic Apps
• Collaborate with stakeholders, analysts, and engineering teams to gather requirements and deliver data solutions
• Monitor, troubleshoot, and optimize data workflows and integrations
• Participate in code reviews, technical discussions, and solution design activities
• Contribute to CI/CD and deployment processes within the Azure environment
• Ensure data quality, security, and performance best practices are followed
   

Requirements

• Strong hands-on experience with Azure Data Factory (ADF)
• Solid experience with Azure SQL and the Azure Data Stack
• Strong Python development skills
• Experience working with Azure Logic Apps and Azure Function Apps
• Good understanding of cloud-based data architecture and integration patterns
• Experience building and maintaining scalable data pipelines
• Familiarity with Azure DevOps, Git, and CI/CD pipelines
• Experience working in Agile development environments
• Strong communication and collaboration skills
• Upper-Intermediate or higher English level

Nice to have

• Experience leading technical initiatives or mentoring engineers
• Knowledge of data governance and security best practices
• Experience with infrastructure automation or monitoring tools
• Exposure to financial services or development finance domains

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