Lead Analytics Engineer — Actuarial, Finance & Investments
Core
Design, build, and maintain scalable data models and ETL/ELT pipelines to provide clean, accurate datasets for Finance, Investment Management, and Actuarial stakeholders.
Role type
Lead Analytics Engineer (Actuarial & Finance Domain)
Builds
Scalable data models, curated datasets, data marts, and cloud-native data architectures for investment and actuarial data.
Domain
Insurance, Actuarial Science, Investment Management, Finance
Deliverable
production ML models | product features | dashboards & analysis
Required skills
Advanced SQL, Python, Data Modeling, ETL/ELT Development, Cloud Data Architecture, Data Governance, Pipeline Orchestration, Technical Mentoring
Preferred skills
Investment Accounting, Actuarial Analytics, Insurance Asset Data, Performance Measurement, Data Product Strategy
Technologies
Snowflake, Databricks, BigQuery, Amazon Redshift, dbt, SQLMesh, Coalesce, Dataform, Dagster, Airflow, Prefect, Azure Data Factory
Responsibilities
Design and optimize cloud-native data architectures; Build robust ETL/ELT pipelines integrating structured and unstructured data; Lead migration of investment data from legacy platforms to modern cloud ecosystems; Mentor junior engineers and establish data engineering best practices; Partner with Finance, Investment, and Actuarial teams to translate business requirements into data solutions; Identify opportunities to create new data products and analytical capabilities.
Seniority
Senior, hands-on IC with leadership responsibilities
