Manage and enhance the client’s Snowflake data warehouse, focusing on structure, performance, and cost optimization.
Design and implement complex SQL and Python transformations at the pandas/polars/numpy level across multiple schemas and data domains.
Analyze existing Snowflake setup and recommend improvements in storage structure, clustering, and performance tuning.
Implement best practices around data partitioning, security, role-based access control, and query performance.
Develop and maintain Python-based data pipelines integrated with AWS and Snowflake.
Write Python scripts and utilities (pandas, polars, numpy) to automate data validation, ingestion, and reporting processes.
Implement and refine dbt models to transform raw data into analytics-ready structures.
Support Tableau dashboard workflows, maintaining and optimizing data sources and extracts.
Participate in knowledge transfer with existing team members to understand architecture, pipelines, and operational processes.
Deliver thorough documentation and ensure smooth handoff post-engagement.

5–8+ years of professional experience as a Data Engineer, Analytics Engineer, or Senior Data Developer, with 1–3 years of experience (or more) in Financial Services.
Strong expertise with Snowflake, including schema design, query optimization, and performance tuning.
Advanced SQL skills, including complex joins, CTEs, window functions, and efficient transformations.
Proficient in Python for data manipulation, pipeline development, and integration with Snowflake and AWS, particularly using pandas, polars, and numpy.
Experience using dbt for transformation and documentation.
Experience with Prefect for job scheduling and workflow management.
Familiarity with Tableau for analytics support and data delivery.
Experience with Microsoft SQL Server.
Comfortable integrating into a mature, existing codebase and collaborating in a fast-paced, cross-functional environment.
Excellent communicator and problem-solver, able to operate independently with clearly defined outcomes.

Data Engineer

Key skills