Senior Data Engineer

We are building an elite, domain-deep data engineering team for a leading global asset & wealth management client. This is not a body-shop role - you will work shoulder-to-shoulder with the client’s Data & AI leadership on investment, risk, and asset-management data platforms. We are looking for exceptionally strong, high-quality engineers who combine modern data engineering craft with genuine capital-markets understanding., * Design and build cloud data pipelines on Azure Data Lake, Azure Data Factory (ADF) and Databricks (ADB) across ingestion * curation (Silver) * Data Access Layer (Gold).

• Implement SCD Type-2, transformation logic, and DAL standardization for investment, risk and AUM datasets.
• Model and engineer data for asset management, portfolio risk, and performance workflows (e.g., Risk, FRM-GA, BarraOne, AUM reporting).
• Build data quality, validation and reconciliation frameworks (source-to-target, QA evidence).
• Collaborate with data scientists and quants to deliver AI-ready, governed data foundations, including agentic / GenAI-assisted engineering.

• 4+ years of hands-on data engineering with strong Python, SQL, Spark/Databricks, and Azure (ADF, ADLS, Synapse).
• Domain experience with investment, asset management, or capital-markets data (portfolios, securities, risk, performance, or reference data).
• Strong data modelling (dimensional, SCD, medallion architecture) and pipeline orchestration.
• Agentic AI / GenAI-assisted development experience (e.g., GitHub Copilot).

Preferred

• CFA charterholder or active CFA candidate (Level I-III) - or equivalent demonstrated investment-domain fluency.

Who You Are

A younger, high-potential professional with an outstanding track record; collaborative, curious, and comfortable working directly with senior client stakeholders in a people-first, partnership culture.

Pulled from the full job description

• 401(k)
• Vision insurance
• Dental insurance
• Life insurance, * 401(k)
• Dental insurance
• Life insurance
• Vision insurance