Senior Data Engineer (EconTech) - Contract

About the role

MAS is expanding its EconTech capability within the Enterprise Knowledge Department to support the Economic Policy Group (EPG). EconTech applies econometrics, data science and artificial intelligence to large datasets on macroeconomic surveillance, inflation, trade, the labour market and financial stability. You will be the team's data engineer, building and running the data foundations that support EconTech and the wider EPG, helping implement EPG's data strategy.

Key responsibilities

• Own the EPG data inventory and standards for acquisition, storage, versioning, documentation and sharing, and partner with economists to turn policy and research needs into prioritised data requirements.
• Work with data owners, platform, governance and security teams to bring data assets onto enterprise infrastructure with appropriate controls.
• Design and operate production-grade pipelines for structured and unstructured data (official statistics, licensed data, high-frequency indicators, web data, document-extracted information) with validation, monitoring and recovery.
• Build research-grade datasets handling revisions, vintages, seasonal adjustment, rebasing and frequency conversion, and develop reusable data products with metadata, lineage and programmatic access.
• Connect pipelines and products to downstream analytical programmes and BI tools.
• Build and validate pipelines that extract structured information from documents and text using text analytics and large language models, and make data assets safely accessible to AI-assisted workflows.
• Promote strong engineering practices, documentation and monitoring, and guide junior engineers.

Required profile

• Bachelor's degree or higher in a relevant quantitative discipline; postgraduate qualifications in Economics or Statistics are an advantage.
• Around 5-8 years of experience in data engineering, data platforms or statistical systems supporting economists or quantitative researchers.
• Experience in central banking, economic policy, official statistics, international organisations or financial-sector research is an advantage.
• Familiarity with macroeconomic and financial datasets, economic time-series issues (vintages, seasonal adjustment, rebasing, nominal vs real values), and how data is used in research and policy analysis.
• Ability to bridge economists and data engineers, work hands-on, and manage multiple priorities in a fast-paced environment.

Required skills

• Strong proficiency in Python/R and SQL.
• Hands-on experience building cloud-based ETL/ELT pipelines, including orchestration and distributed processing frameworks.
• Integrating structured and unstructured data from APIs, files, databases, feeds and web sources, with time-series and panel data modelling.
• LLM-based information extraction, data governance, Git, testing, CI/CD, logging and monitoring.

The contract ends in December 2028. Applicants submit a CV highlighting data engineering and data product experience, and are encouraged to include a brief description of a pipeline or dataset they built for economic, financial or statistical analysis.