Data Engineer (Snowflake)

Our data team has expertise across engineering, analysis, architecture, modeling, machine learning, artificial intelligence, and data science. This discipline is responsible for transforming raw data into actionable insights, building robust data infrastructures, and enabling data-driven decision-making and innovation through advanced analytics and predictive modeling.
A Senior Data Engineer responsible for hands-on execution and technical leadership of a high-scale Trade & Positions data lake / data platform for a Private Credit, Trading-oriented business.

The role focuses on enhancing and extending an existing Snowflake-based Data Vault + Dimensional architecture, delivering near-real-time (<5 min) pipelines, and ensuring enterprise-grade data quality, data lineage, and governance for downstream analytics in Power BI / Sigma or other similar projects for this US Private Credit client.
This engineer will work across Trades, Positions, GL, and Reference Data, handling high-volume CDC, cancel/correct logic, and billion-row fact tables, while partnering closely with platform, analytics, and business stakeholders.
Responsibilities:
- Design, build, and operate scalable data pipelines for trading, positions, and financial data
- Develop and maintain enterprise data models supporting analytics and reporting
- Implement near-real-time data processing and incremental change handling
- Ensure data quality, reconciliation, and auditability across financial datasets
- Optimize Snowflake performance, cost, and reliability at scale
- Establish and follow engineering best practices including CI/CD and version control
- Partner with analytics and business teams to deliver trusted, performant datasets
- Contribute to data governance, lineage, and security standards

Required:
- 7+ years of experience in data engineering on modern cloud data platforms
- Strong expertise with Snowflake and advanced SQL
- Hands-on experience with dimensional modeling and historical data handling
- Experience with Data Vault modeling or lakehouse architectures
- Experience building reliable, production-grade data pipelines at scale
- Background in trading, private credit, or capital markets data
- Understanding of financial concepts such as trades, positions, GL, and PnL
- Experience with data quality, reconciliation, and operational monitoring
- Strong communication skills and ability to work across engineering and business teams

Preferred / Desired
- Experience with Coalesce, dbt, or similar transformation tools
- Experience with Fivetran for SaaS ingestion or similar platforms
- Familiarity with CDC-based ingestion patterns and near-real-time pipelines
- Experience with data governance, lineage, and cataloging tools (e.g., Alation)
- Exposure to Power BI, Sigma, or similar analytics platforms