We're rebuilding Cegeka's data foundation by migrating our legacy analytics platform to a modern cloud-based and domain-oriented architecture on Databricks. This shift requires engineers who can keep business-critical legacy workloads reliable while helping us redesign and migrate them into modern, cloud-based production systems.

That’s why we are not looking for someone who only wants to build new solutions from a clean slate; we are looking for someone who understands established platforms, can navigate complex legacy logic and dependencies, and can turn that knowledge into stable, maintainable data and analytics solutions on our future cloud platform.

This role is for someone who can demonstrate hands-on experience working with legacy data systems and migrating them to modern cloud-based production environments. Experience migrating SQL Server workloads, including data, pipelines, business logic, and operational processes, to Databricks will give you a clear edge over other candidates.

If you are a pragmatic Data or Analytics Engineer who understands both legacy and modern data platforms, have experience working in an environment in transition and want to help shape a new cloud-based data foundation from the ground up, read on.

What you will be working on

As a Data or Analytics Engineer, you will initially own and maintain the data workloads within our SQL Server data warehouse that support Cegeka's critical business processes. You will keep the existing environment reliable by maintaining and enhancing jobs, resolving incidents, improving performance and quality, and supporting changes requested by stakeholders. At the same time, you will build a thorough understanding of its data, business logic, dependencies, and operational processes. Once the migration begins, you will contribute hands-on to implementing, validating, and transitioning these workloads to our new Databricks platform while safeguarding business continuity throughout the change.

What you will do

Concretely this means you will …

• Update SQL stored procedures, jobs, and SSIS packages to implement business logic changes requested by stakeholders


• Improve performance and quality by optimizing ingestion and transformation jobs to ensure data workloads complete on time and without errors


• Investigate failed jobs, identify root causes in the existing business logic, and implement appropriate solutions


• Support analysts and help architects define improvements to observability, quality, and performance


• Resolve incidents promptly and document improvements that strengthen platform stability


• Build deep knowledge of your team’s data domain to prepare workloads for an efficient migration to Databricks


• Rebuild SQL Server and SSIS workloads on Databricks, including ingestion, transformation, orchestration, testing, validation, deployment, and production transition


• Apply modern engineering standards to build, test, deploy, monitor, and support data workloads across the legacy environment and future cloud platform

We are looking for someone with ...

• Professional experience with SQL Server, SSRS, SSAS, and SSIS


• Experience building and operating data workloads on Databricks using PySpark, Spark SQL, Delta Lake, Databricks Workflows, and Medallion architecture


• A strong understanding of data warehousing principles, ETL/ELT, and data modeling techniques


• Proficiency in performance tuning and query optimization through execution plans, indexes, and statistics management


• Experience reverse engineering complex legacy data systems and documenting undocumented business logic, data flows, dependencies, and operational processes


• Experience migrating data workloads between platforms and validating data quality, business logic, performance, and operational continuity


• Experience contributing or giving feedback on the design of new data products and data workloads, including architecture, data models and integration patterns