Data engineer

This role is for a Modern Data Engineer with strong software engineering skills who can build and deploy cloud-native data platforms. Key Requirements Software Engineering Strong Python development skills (primary programming language) Solid understanding of software engineering principles and clean coding practices Experience working within the Software Development Life Cycle (SDLC) Proficient with Git and version control Experience with CI/CD pipelines and modern Dev Ops practices Ability to solve problems through code, not just SQL Hands-on experience with modern data engineering technologies, including: Spark / Py Spark Databricks Kafka Flink Data Lake architectures Experience building both batch and streaming data solutions

Practical experience delivering solutions on at least one major cloud platform:

Amazon Web Services (AWS) Relevant services may include: Data processing and analytics tools (Big Query, Synapse, Redshift, Databricks, Dataflow, Glue, EMR, Dataproc) Event streaming platforms (Pub/Sub, Event Hubs, Kinesis) Container platforms (GKE, AKS, EKS) Dev Ops & Deployment

Experience with:

Docker Infrastructure as Code (Terraform or similar) Monitoring and observability tools

Experience should be gained through real production projects, not certifications alone.

Additional Valuable Skills Data modelling (relational and dimensional) Data warehousing concepts Modern orchestration and data platforms such as Databricks, Kafka and Microsoft Fabric Ideal Candidate

We're looking for a modern data engineer with a software engineering mindset. Candidates should have proven experience delivering cloud-based data solutions using Python, Spark, CI/CD, Git and modern data platforms. Experience limited to traditional SQL, SSIS or ETL development without modern engineering practices is unlikely to meet current client requirements.

What We Value Continuous learning and professional development Ability to contribute immediately within a modern engineering environment Client-facing consulting experience is advantageous #J-18808-Ljbffr