Data Engineer (AI)

Company Summary Gresham is a global financial services technology company specialising in enterprise data automation. We help financial institutions ensure that their operational, regulatory and management data is complete, accurate, timely and fully auditable — particularly within complex environments where data is distributed across multiple systems. Our solutions automate data controls, reconciliations, workflows and exception management, enabling clients to reduce operational risk, strengthen data governance and enhance confidence in reporting across highly regulated environments. Serving both buy-side and sell-side organisations worldwide, Gresham partners with clients to deliver trusted, transparent and resilient data operations. We are seeking an

AI Data Engineer to build scalable data platforms that power analytics, machine learning, and Generative AI (LLM/RAG) use cases. This role combines data engineering, cloud, and AI/ML capabilities to enable intelligent data pipelines, agentic workflows, and real-time data processing.

Job Responsibilities

• Design and build scalable ETL/ELT pipelines using Python, SQL, Airflow, DBT, and Spark.
• Develop data platforms on AWS (S3, Glue, EMR, Lambda, SQS, EventBridge).
• Build and optimize RAG pipelines (embeddings, vector DBs like FAISS/Pinecone).
• Enable LLM-based and agentic workflows (LangChain, CrewAI, AutoGen).
• Implement event-driven and real-time data pipelines.
• Design data lake/lakehouse architectures (Iceberg/Delta Lake).
• Ensure data quality, lineage, and observability (OpenMetadata or similar).
• Support ML pipelines, feature engineering, and model retraining workflows.
• Implement CI/CD and containerized deployments (Docker).
• Optimize and productionize existing data workflows.

Job Requirements

• 4–9 years of experience in Data Engineering / AI Data Engineering
• Strong Python (Pandas, NumPy) and advanced SQL
• Hands-on with Airflow, DBT, Spark (EMR/Glue)
• Experience with AWS data stack (S3, Glue, Lambda, EMR, etc.)
• Understanding of LLMs, embeddings, and RAG architectures
• Experience with vector databases (FAISS, Pinecone, etc.)
• Knowledge of data lakes/lakehouse (Iceberg/Delta)
• Experience with relational/analytical DBs (Snowflake, Oracle, SQL Server)
• Familiarity with CI/CD, Docker, Infrastructure-as-Code, and DevOps practices and automation tools.

Preferred Skills

• Experience with Trino/Presto
• Exposure to OpenMetadata or data governance tools
• AWS certifications
• Experience in real-time/streaming pipelines
• Exposure to product engineering environments

Equal Opportunities Statement At Gresham, we are committed to building a diverse and inclusive workforce that reflects the communities we serve. We actively encourage applications from individuals of all backgrounds and are dedicated to providing a workplace where everyone feels valued, respected and supported. We make employment decisions based on merit, skills and potential, and do not discriminate based on any protected characteristic. We are also committed to making reasonable adjustments throughout the recruitment process and employment lifecycle.