Lead Analytics Engineer — Actuarial, Finance & Investments
Tasks
- Apply SQL and Python to design data transformations and automate workflows
- Build robust ETL and ELT pipelines for structured and unstructured data
- Create curated datasets and data marts for business users
- Create data products and analytical capabilities
- Design build and maintain scalable data models
- Develop and optimize cloud native data architectures
- Establish data engineering best practices for modeling testing documentation and governance
- Lead migration and transformation of investment data from legacy to cloud
- Mentor analytics engineers with code reviews and architectural guidance
- Optimize data warehouse performance schema design access controls and orchestration
- Serve as subject matter expert for investment and actuarial data domains
- Translate business requirements into scalable data solutions
Perks/Benefits
Skills/Tech-stack
Airflow | Amazon Redshift | Attribution Analytics | Azure Data | Azure Data Factory | BigQuery | DBT | Dagster | Data Factory | Data Governance | Data Management | Data Modeling | Data Quality | Data Warehousing | Data pipeline | Data pipeline orchestration | Databricks | Dataform | ELT | ETL | Insurance Data | Insurance data management | Investment accounting | Pipeline Orchestration | Prefect | Python | SQL | Snowflake
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
Analytics | Analytics Engineer | Engineer | Lead | Lead Analytics | Lead Analytics Engineer
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