Description

Role Overview
We are seeking an experienced Senior Data Engineer with strong expertise in SQL, Data Warehousing, and Snowflake to join our Capital Markets technology team. The ideal candidate will play a key role in designing, developing, and optimizing enterprise-scale data platforms and analytical solutions that support trading, risk management, regulatory reporting, market data, and other capital markets functions.
This role requires hands-on experience building high-performance data pipelines, modern cloud-based data warehouses, and scalable ETL/ELT solutions. Candidates with a strong understanding of Capital Markets products and workflows will be highly preferred.

Key Responsibilities
• Design, develop, and maintain scalable data engineering solutions and data pipelines.
• Build and optimize enterprise Data Warehouse solutions using Snowflake.
• Develop efficient and complex SQL queries, stored procedures, views, and data transformation logic.
• Create and support ETL/ELT frameworks for ingesting and processing large volumes of financial data.
• Collaborate with business analysts, traders, risk teams, and data consumers to understand data requirements.
• Design data models that support reporting, analytics, and regulatory compliance needs.
• Ensure data quality, integrity, governance, and security across the data ecosystem.
• Troubleshoot performance bottlenecks and optimize database and warehouse performance.
• Participate in architecture discussions and recommend best practices for data engineering and cloud adoption.
• Support production deployments and manage ongoing enhancements to data platforms.
• Create technical documentation, data lineage, and operational support procedures.

Required Qualifications
• Bachelor's degree in Computer Science, Engineering, Information Systems, or related discipline.
• 8+ years of experience in Data Engineering, Data Warehousing, or related roles.
• Strong Capital Markets domain knowledge.
• Deep understanding of market data, reference data, trading systems, risk, securities, fixed income, equities, derivatives, or front-to-back-office processes.
• Experience working in Agile delivery environments.

Must-Have Technical Skills
SQL

• Expert-level SQL development experience.
• Complex joins, analytical functions, window functions, stored procedures, and query performance tuning.
• Data reconciliation and optimization of high-volume datasets.

Data Warehouse

• Strong experience designing and implementing Data Warehouse solutions.
• Dimensional modeling.
• Star schema and Snowflake schema design.
• Data Mart architecture.
• Data integration and historical data management.

Snowflake

• Hands-on Snowflake development and administration experience.
• Snowflake architecture and performance optimization.
• Data loading and transformation using Snowflake.
• Snowpipe, Streams, Tasks, Time Travel, and Cloning concepts.
• Security, role-based access, and data governance within Snowflake.

Python / PySpark

• Experience developing data ingestion and transformation pipelines.
• Data processing using PySpark.
• API integration and automation.
• Data validation and quality frameworks.
• Performance tuning of Spark workloads.

Good-to-Have Skills
SSIS

• Experience developing and supporting SSIS packages.
• Legacy ETL migration to modern cloud platforms.
• Scheduling and monitoring ETL workflows

Key Skills

Education

Any Graduate