Core Data Engineering

• Strong programming proficiency in Java (preferred) or Python.

• Hands-on experience with at least one of: Kafka, Flink, Spark (Flink/Kafka preferred for streaming).

• Solid understanding of stream processing concepts (e.g., event time, state, backpressure).

• Understanding of software engineering best practices: testing, design patterns, CI/CD, Git.

• Experience building ETL/ELT or streaming data pipelines.

• Exposure to microservices and distributed system concepts.

• Experience working with cloud platforms, ideally AWS, but Azure/GCP also acceptable.

• Understanding of distributed compute, large-scale data systems, and performance considerations.

DevOps & Engineering Practices

• Experience with CI/CD tools (Azure DevOps, GitHub Actions, Jenkins etc.).

• Infrastructure‑as‑Code (Terraform preferred).

• Experience with containerisation (Docker) and orchestration platforms (Kubernetes/EKS).

Certifications & Tools

• Exposure to enterprise data platforms (Databricks, Snowflake, BigQuery, or similar).

• Cloud certifications (AWS, Azure, GCP) are beneficial but not required.

Other Requirements

• Minimum 3 years’ experience working on data engineering or large-scale data solutions.

• Comfortable working in Agile delivery teams.

• Strong communication skills and ability to collaborate with technical and non‑technical stakeholders.

Desirable

• Experience in client-facing or consulting environments.

• Professional cloud or data engineering certifications.

• Experience mentoring or supporting junior engineers.

• Background in designing or operating real‑time, low-latency systems.

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