JOB  SUMMARY

What you will be doing…

• Own pipeline code, DBT models, and SQL transformations end-to-end; uphold team-level quality standards and act as first reviewer for junior PRs
• Direct AI agents through complex, multi-step data engineering tasks; contribute effective prompts and orchestration patterns to the shared team prompt library
• Evaluate AI-generated pipeline code, SQL, and dbt models for correctness, performance, security, and architectural alignment before merge
• Build and maintain high-performance Snowflake pipelines — including schema design, RLS policies, query optimisation, cost management, and warehouse sizing
• Design, develop, and maintain dbt models, tests, macros, and packages at production scale
• Administer and tune AWS RDS databases across Postgres, MySQL, and MS SQL — schema design, performance tuning, query optimisation, index management, and backup/recovery
• Build and maintain AWS-based data infrastructure using S3, Glue, Lambda, Kinesis, and EMR; apply IaC practices (Terraform or CloudFormation)
• Manage workflow orchestration using Apache Airflow or equivalent, including retry strategies, observability, and production-grade reliability patterns
• Design and implement automated data quality monitoring and validation frameworks; own data quality incidents from detection through to resolution and postmortem
• Own ISO 27001 evidence collection for team pipelines and data assets; implement RLS, masking, and data access controls for sensitive HR and employee data
• Mentor junior Data Engineers through PR review, pairing, and structured feedback

Skills and Experiences:
Must haves:

• Strong AWS RDS DBA experience across Postgres (Aurora), MySQL (Aurora), and MS SQL — schema design, query optimisation, index management, performance tuning, and backup/recovery
• Solid data engineering experience, ideally with a DBA background who has expanded into the modern data stack (Snowflake, dbt, Python)
• Deep, hands-on Snowflake experience — query optimisation, cost management, RLS, schema design, and performance tuning
• Proficient with DBT (models, tests, macros, packages) at production scale
• Strong Python scripting and advanced SQL for transformations, automation, and tooling
• Hands-on with AWS data services (S3, Glue, Lambda, Kinesis, EMR) and IaC (Terraform or CloudFormation)
• Demonstrated experience building tools or automations using AI — Claude Code, GitHub Copilot, multi-step prompting, or multi-agent orchestration
• Strong workflow orchestration experience (Apache Airflow, AWS Step Functions, or equivalent)
• Familiarity with ISO 27001 data security obligations and compliance-aware data engineering practices
• Strong written and verbal communication; comfortable engaging with non-technical stakeholders across Analytics, Product, and the business

Nice to have:

• Experience with Apache Kafka and Apache Flink — consumer/producer patterns, partition strategies, CDC, and schema evolution
• Exposure to AI/ML data pipelines — embedding generation, vector store ingestion, Bedrock knowledge base preparation, or training data management
• Industry certification: SnowPro Advanced: Data Engineer, AWS Data Analytics Specialty, dbt Advanced, or equivalent

Are you interested in this position?

Apply by clicking on the “Apply Now” button below!

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