Data Engineer

Overview

We are seeking a skilled Data Engineer to join our data team. The role involves managing and enhancing enterprise data warehouses, creating data pipelines to integrate third-party data, monitoring daily data loads, improving integration processes, and developing comprehensive data quality and monitoring tools.

This position requires a collaborative team player who can work across different business functions, quickly learn complex concepts, and communicate effectively with both technical and non-technical stakeholders. The ideal candidate is detail-oriented, self-motivated, curious, and able to perform under time-sensitive deadlines.

• Manage and enhance SQL Server–based enterprise data warehouses.
• Design, develop, and maintain ETL/SSIS workflows and APIs for ingesting external data sources.
• Translate complex business requirements into clear technical specifications.
• Monitor daily and month-end data warehouse processes and resolve issues promptly.
• Perform SQL Server tuning and warehouse performance optimization.
• Reconcile data from various sources and consolidate into data marts.
• Develop and maintain SSAS Tabular models or cubes for reporting needs.
• Document data logic, processes, key datasets, and data flows.
• Contribute to modern data platform initiatives using tools such as Python, Spark, DuckDB, Delta Lake, and related technologies.
• Implement data quality checks, validations, and anomaly detection frameworks.
• Support the development of metadata catalogs, data lineage tracking, and data governance processes.
• Assist with infrastructure support and participate in future-proofing and cloud integration efforts.

• Bachelor’s degree in Computer Science or related field.
• 3–5 years of experience with SQL, data warehousing, SSIS, SQL Server, cloud databases, and Python.
• Strong understanding of data modeling methodologies.
• Proven experience creating, debugging, and optimizing ETL processes.
• Skilled in handling large datasets and query optimization.
• Effective at working with business teams to capture and implement requirements.
• Strong written and verbal communication skills.
• Experience with analytics and visualization tools, SSAS, or equivalent platforms.
• Familiarity with Parquet, Delta Lake, Apache Arrow, or similar formats.
• Experience with Spark, Pandas, Polars, dbt, DuckDB, or Databricks is a plus.
• Exposure to metadata/cataloging tools and version control (Git) and CI/CD.

• Associate

• Full-time

• Data Engineering

• Investment Management