Senior Data Engineer — AI-Powered Data Platform (Hybrid)

Airswift; Birmingham; Hybrid; GBP 101,000 - 166,000; Full time

Job summary

Airswift is looking for a Senior Data Engineer in Birmingham to design, build and optimise enterprise-scale data platforms that support AI, ML and advanced analytics. The role is a contract, full-time workload with a hybrid setup (3 days onsite).

You will develop high-throughput data pipelines using Spark and AWS services, implement lakehouse architectures, and ensure governance, security and observability across large datasets.

Qualifications

• Minimum 5 years in data engineering or equivalent.
• Strong Spark development in Java/Scala.
• Hands-on AWS experience (S3, EMR, Glue, IAM).
• Advanced SQL for complex transformations.
• Experience building ETL/ELT pipelines & lakehouse solutions.
• Exposure to AI/ML data ecosystems.
• Solid data governance, security & resilience practices.

Responsibilities

• Design, build, and maintain high-throughput data pipelines with Spark.
• Develop scalable ETL/ELT solutions for structured/unstructured data.
• Support AI/ML/Generative AI initiatives with data platforms.
• Implement lakehouse architectures for scalability and analytics.
• Optimize SQL transformations across large datasets.
• Enforce data governance, security, monitoring and reliability.
• Collaborate with cross-functional teams to boost automation and observability.

Skills

5+ years of Data Engineering

Spark Java/Scala

AWS (S3, EMR, Glue, IAM)

Advanced SQL

ETL/ELT pipelines

AI/ML data ecosystems

Data governance & security

Snowflake

Observability & DevOps

Tools

Snowflake

Observability tools

DevOps practices

Job description

Airswift is looking for a Senior Data Engineer in Birmingham to design, build and optimise enterprise-scale data platforms that support AI, ML and advanced analytics. The role is a contract, full-time workload with a hybrid setup (3 days onsite).

You will develop high-throughput data pipelines using Spark and AWS services, implement lakehouse architectures, and ensure governance, security and observability across large datasets.