We are a global technology company focused on AI and digital engineering. We combine expertise in software, hardware, data and artificial intelligence with product strategy, design and technology consulting.

We help global enterprises and innovative startups design and develop complex digital products, modernize technology platforms and accelerate their AI transformation.

The company brings together several thousand technology professionals across an international network of development and business centers in multiple countries. We work with leading global organizations across a wide range of industries.

Our company culture is built around innovation, high quality, continuous learning, open communication and personal ownership. Employees work in international, multidisciplinary teams on technologically demanding projects and products that create real-world impact.

We are looking for an experienced Data Engineer with extensive practical experience with data platforms built on Databricks. The position focuses on creating, optimizing, and operating scalable data pipelines, data lakes, and Lakehouse solutions that support advanced analytics and data products.

You will work with complex data processing, third-party integrations, ETL/ELT pipelines, and orchestration of data tasks in a cloud environment. If you enjoy Databricks, Apache Spark, large datasets, and modern cloud technologies, and are not limited to just one programming language or tool, this role could be ideal for you.

• Take responsibility for functionalities in the area of data engineering, technical architecture, and code quality.
• Design, implement, and manage data pipelines and workflows built on Databricks.
• Create and optimize ETL/ELT processes using Apache Spark on the Databricks platform.
• Design and manage data lakes and Lakehouse architecture using Delta Lake.
• Integrate various data sources and ensure reliable data ingestion.
• Automate orchestration, scheduling, and monitoring of Databricks tasks.
• Design scalable data processes resilient to failures.
• Ensure high quality, consistency, and accuracy of data across the platform.
• Decide on the appropriate data storage methods, computing resources, and performance optimization.
• Collaborate with analytics, BI, and business teams on the development of data products.

• At least 7 years of relevant experience in the position of Data Engineer.
• Strong practical experience with Databricks and Apache Spark.
• Very good knowledge of Python or Scala, ideally both languages.
• Very good knowledge of SQL, relational databases, and data warehouse principles.
• Practical experience with ETL/ELT and designing data pipelines.
• Experience with cloud platforms Azure, AWS, or GCP, ideally with running Databricks workloads.
• Experience with distributed systems and large-scale data processing.
• Familiarity with Unix operating systems.
• Experience with version control systems.
• Very good communication skills and knowledge of English.

An advantage will be

• Databricks certification at the Professional level.
• Experience with Delta Lake, performance, and cost optimization.
• Experience with streaming technologies, such as Apache Kafka.
• Knowledge of workflow orchestration tools, such as Databricks Workflows or Apache Airflow.
• Experience with cloud-native and serverless data architecture.
• Knowledge of Docker, Kubernetes, and virtualization.
• Experience in creating data products that support analytics and business decision-making.

• Databricks at scale – you will not only create simple integration tasks but also extensive data platforms, pipelines, data lakes, and Lakehouse solutions.
• High degree of technical influence – you will take responsibility for functionalities, architecture, code quality, and decisions regarding performance, storage, and computing resources.
• Modern data stack – Databricks, Apache Spark, Delta Lake, Python, Scala, cloud, orchestration, streaming, and distributed data processing.
• Real business impact – the data created will not just end up in storage but will directly support analytics, data products, and customer decision-making.
• Complex projects for global clients – client works on technologically demanding solutions across semiconductors, finance, insurance, healthcare technology, telecommunications, and other industries.
• Collaboration with experienced professionals – working with senior engineers, solution architects, and data and AI specialists who openly share their knowledge.
• Support for professional development – learning budget, mentoring, conferences, and certifications including Databricks and Anthropic programs, the costs of which are covered by client.
• Technical and managerial career path – the opportunity to deepen technical expertise, lead a team, mentor colleagues, or broaden experiences across engineering, data, AI, and product.
• Flexibility – depending on the specific project and location, client offers hybrid or remote collaboration and flexible working hours.
• Support for health, family, and quality work – the offer may include health insurance, sports activities, family programs, and recognition of exceptional contributions.

The biggest attraction of the role is the combination of working with the modern Databricks stack, truly large-scale data, and the opportunity to influence the final solution from architecture to its production operation.

• We are a reliable and stable company with an international reach
• If a project ends, we immediately offer another one
• We have projects from more than 200 different companies
• We guarantee timely invoice payments and minimal administration
• We organize great company events for our entire IT community
• We provide free accounting and tax consulting
• We pride ourselves on a personal approach and fairness, you can rely on us