Data Engineering, Director

Key Responsibilities
Team Leadership & Mentorship: Lead and mentor a distributed team of data and platform engineers, fostering a culture of technical excellence, accountability, and professional growth.

High-Performance Data Solutions: Oversee the design and implementation of ETL/ELT pipelines using Cloud Data warehouses like Snowflake ensuring data quality and compliance for multi-terabyte scale data stores.

Advanced Analytics & ML Integration: Drive the integration of advanced data science workflows, leveraging cloud-native ML services to enhance predictive models and analytical dashboards.

Stakeholder & Customer Success: Partner with investment, risk, and product teams to translate complex business requirements into high-performance database solutions.

Infrastructure Management: Guide best practices for cloud infrastructure (Azure or AWS) and containerized data services (Enterprise-grade container orchestration platform supporting declarative infrastructure and horizontal scaling, Snowpark Container Services).

Advanced Troubleshooting & Post-Mortems: Lead deep-dive post-mortem analysis and provided architectural solutions for highly complex database issues.

Required Qualifications

• 15+ years of progressive experience in Data Engineering, Database Architecture, and Distributed Systems, with significant time spent in a technical lead role.

• Proven expertise in modern data warehousing technologies, specifically Snowflake

• Hands-on experience with managing a variety of database flavors(OLTP, Cloud native Datawarehouse, distributed column stores) and Query engines at massive scale.

• Strong background in cloud infrastructure and services, either AWS/Azure.

• Demonstrated ability to perform database design, SQL tuning, and query optimization for both OLTP and OLAP systems.

• Strong expertise at writing complex SQL and Python.

• Experience of building analytics with full-stack data science and data visualization tooling like Numpy, Pandas, Matplotlib and Streamlit.

• Knowledge and experience working in classical or modern Machine learning projects preferred but not necessary.

• Experience closely working with ML Engineers.

• Master’s or Bachelors in Computer Science/Maths/Statistics.

• Manage database objects such as schemas, tables, indexes, triggers, and views

• Ensure high availability, reliability, and data integrity of databases

• Perform regular database maintenance and health checks

• Support production databases and resolve data‑related incidents

• Monitor database performance and system health

• Identify and resolve performance bottlenecks

• Tune SQL queries, indexes, and database configurations

• Assist development teams with query optimization and schema design

• Maintain documentation for database configurations and procedures

• Strong expertise in PostgreSQL architecture and internals

• Advanced knowledge of SQL and PL/pgSQL

• Experience with performance tuning and monitoring tools

• Familiarity with Linux/Unix environments

• Scripting skills (Bash, Python, or similar)