Senior Data Engineer

Firm OverviewLunate is a new Abu Dhabi-based, Partner-led, independent global alternative investment manager with more than 250 employees and $115 billion of assets under management. Lunate invests across the entire private markets spectrum including buyouts, growth equity, early and late-stage venture capital, private credit, real assets, and public equities and public credit. Lunate aims to be one of the world’s leading private markets solutions providers through SMAs and multi-asset class funds, seeking to generate best-in-class risk-adjusted returns for its clients.Job PurposeThe Senior Data Engineer will be the first dedicated internal data engineering hire in Lunate’s Data & AI function. This role is responsible for building dependable ingestion and transformation pipelines into Snowflake, shaping high-quality, well-modelled datasets that power reporting, operations, and AI-enabled products. You will work closely with the Head of Data & AI and partner with Infrastructure (who own Snowflake account and platform setup) to deliver a modern, data-as-code engineering practice with strong controls, testing, and repeatability, supporting both BI and AI/Agentic workloads.Key Duties and ResponsibilitiesBuild and own ingestion pipelines into Snowflake using modern ELT patterns (Fivetran or equivalent, plus custom ingestion where needed), handling schema drift and source changes safely.Leverage AI Tools to design and automate our pipelines.Implement a layered data architecture (raw, standardised, business) that preserves immutability, auditability, and supports reprocessing and backfills.Develop transformations as version-controlled code (SQL and Python) using dbt or equivalent tooling.Apply pragmatic data modelling practices, using dimensional (Kimball) or relational approaches where appropriate.Build data quality and reconciliation into pipelines, with automated checks and visible quality signals.Operate pipelines like software: CI/CD, automated testing, peer review, and controlled promotion across environments.Optimise Snowflake usage for performance and cost, working with Infrastructure on governance controls.Partner with BI practitioners and AI engineers to deliver AI-ready datasets with consistent semantics and clear lineage.Collaborate with investment, operations, and finance teams to translate requirements into robust data products.Contribute to engineering standards, patterns, and documentation as the data function scales.Qualifications and Experience6+ years of professional data engineering experience delivering production pipelines.Strong experience with Snowflake’s full suite of products – especially core functionality.Hands-on experience with dbt, including testing and environment management.Familiarity with modern ingestion tools such as Fivetran.Strong grounding in data modelling fundamentals (Kimball and relational).Python-native, comfortable writing production-quality pipeline and orchestration code.Strong software engineering discipline applied to data (Git, CI/CD, automated testing).Experience building replayable, idempotent pipelines with backfill support.Financial services experience preferred, with understanding of audit, restatement, and as-of data concepts.