Data Engineer - Investment Experience

Title: Sr. Data Engineer with Investment domain experience

Location: Holmdel, NJ / Hudson Yards, NYC / Bethlehem, PA

Duration: 6+ month

Job Summary

The Senior Data Engineer will design, develop, and support scalable enterprise data solutions for Clients Investments organization. The role will build high-performing data pipelines and data platforms that deliver reliable investment data for reporting, analytics, and downstream business processes.

The engineer will work with investment data across multiple asset classes, including fixed income, equities, commercial mortgage loans, private assets, and derivatives. The role requires strong expertise in modern data engineering, investment data, data quality, and production support, along with the ability to collaborate with product owners, architects, business stakeholders, and engineering teams in an Agile environment.

Qualifications & Required Skills

Must Have Skills

Data Engineering and SQL

• Strong experience in SQL development, complex query design, performance tuning, and large-scale data processing.
• Proven experience designing scalable data pipelines and database solutions that support high-volume integration, reporting, and analytics workloads.
• Strong knowledge of relational, dimensional, and analytical data modeling.
• Experience implementing data quality, validation, reconciliation, exception handling, auditability, and restart and recovery capabilities.

Databricks, Spark, and Python

• Strong hands-on experience with Databricks, Apache Spark, PySpark, and distributed data-processing frameworks.
• Experience developing common frameworks for ingestion, transformation, validation, logging, monitoring, and automation.
• Knowledge of Lakehouse architecture and cloud-based data engineering patterns.
• Experience optimizing Spark jobs, partitioning strategies, storage formats, and pipeline performance.
• Strong Python development skills with experience building reusable, modular, testable, and production-ready data engineering solutions.

ETL/ELT and Orchestration

• Experience designing and implementing enterprise-scale ETL/ELT pipelines using Informatica or equivalent data integration platforms
• Experience building workflows with robust scheduling, dependency management, error handling, recovery, and operational monitoring.
• Experience with enterprise scheduling and orchestration tools such as Control-M or comparable platforms.

Investment Data

• Strong understanding of investment data, including securities, trades, transactions, positions, holdings, cash, pricing, valuations and benchmarks.
• Familiarity with multiple asset classes, including fixed income, equities, commercial mortgage loans, private equity, private placements, and derivative products.
• Understanding of security master, reference data, market data, investment accounting, and downstream reporting processes.
• Ability to translate investment business rules into technical mappings, transformation logic, and validation controls.

DevOps and Delivery

• Experience with Git-based version control and CI/CD platforms such as Azure DevOps, Jenkins, or GitHub Actions.
• Experience with automated testing, deployment, release management, and environment configuration.
• Experience working in Agile delivery environments using Scrum, Kanban, or SAFe practices.
• Strong collaboration skills with product owners, architects, business stakeholders, quality assurance teams, and engineers.