Job Description
We are seeking a Lead Data Engineer to design, build, and scale our enterprise data platform supporting analytics, reporting, and investment decision-making across asset classes. This role combines technical leadership with hands-on development, focusing on data architecture, pipeline design, and governance for high-quality, reliable financial data. You will be acting as a liaison between business stakeholders and the engineering team.
Responsibilities:
- Lead the design and implementation of modern data pipelines and ETL/ELT frameworks using cloud and on-prem environments.
- Architect and manage data models, warehouses, and lakehouses to support analytics, reporting, and machine learning.
- Collaborate with investment, risk, and technology teams to define data requirements and ensure consistency across systems.
- Drive best practices in data quality, lineage, and governance.
- Mentor engineers and set standards for performance, security, and scalability.
- Evaluate and implement new data technologies to improve efficiency and insights delivery.
Qualifications:
- 7+ years of experience in data engineering, with 2+ in a technical leadership role.
- Strong expertise in SQL, Python, and modern data platforms (e.g., Azure Data Factory, Databricks, Snowflake, Synapse, AWS Glue, or GCP BigQuery).
- Experience with data modeling, ETL/ELT pipelines, and data warehousing principles.
- Familiarity with financial or investment data (portfolio, risk, performance, or accounting) preferred.
- Strong understanding of CI/CD, version control (Git), and DevOps for data workflows.
- Excellent communication and cross-functional collaboration skills.
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