Data Engineer
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Summary
Contract Senior Data Engineer working hybrid (3 days onsite in Birmingham) to design and optimise enterprise-scale data platforms, building high-throughput pipelines and lakehouse architectures that support AI/ML and analytics. Core stack is Apache Spark with Java or Scala, AWS services (S3, EMR, Glue, IAM), and advanced SQL.
Duration: Contract
Workload: Full time hours
Setup: Freelance (Daily Rate / Limited Company / Umbrella / Sole Trader)
Location: Birmingham (Hybrid, 3 days onsite)
Our client is seeking a Senior Data Engineer to design and optimise enterprise-scale data platforms that support AI, Machine Learning, and advanced analytics initiatives.
Key Responsibilities:
- Design, build, and maintain high-throughput data pipelines using Apache Spark and cloud-native AWS technologies.
- Develop scalable ETL/ELT solutions for structured and unstructured data.
- Support AI/ML and Generative AI initiatives by enabling robust, data-driven platforms.
- Implement modern lakehouse architectures to improve scalability, resilience, and analytics capabilities.
- Optimise SQL-based data transformations and processing performance across large datasets.
- Ensure best practices around data governance, security, monitoring, and reliability.
- Collaborate with cross-functional engineering teams to improve automation, observability, and platform performance.
Must-Have Skills:
- 5+ years of Data Engineering experience.
- Strong Apache Spark development skills using Java or Scala.
- Hands-on experience with AWS services such as S3, EMR, Glue, and IAM.
- Advanced SQL expertise.
- Experience building ETL/ELT pipelines and data lakehouse solutions.
- Exposure to AI/ML or Generative AI data ecosystems.
- Strong understanding of data governance, security, and operational resilience.
Nice-to-Have:
- Snowflake experience.
- Knowledge of observability tooling, automation, and DevOps practices