Data Engineer

Role: Data Engineer

Location: Palo Alto, New York, San Francisco, Austin, Boston, Boulder, Century City, Delaware, Los Angeles, Salt Lake City, San Diego, Seattle, Washington, D.C – Occasional Onsite required

Duration: Fulltime

Essential Duties and Responsibilities:

• Adapt and optimize firm-standard ETL/ELT data pipelines to ensure accurate and timely data integration to and from firm data repositories.
• Manage finance-related data models, schemas, and structures to support analytics and reporting needs.
• Build and maintain reporting solutions and dashboards using BI platforms such as Power BI or SSRS.
• Translate complex business requirements into intuitive and actionable reports.
• Partner with business stakeholders to define KPIs and ensure consistent reporting standards.
• Integrate firm-level information security policies and processes to ensure data accuracy, integrity, and security.
• Monitor and troubleshoot data workflows, ensuring performance optimization.
• Support firm data governance practices and DLP policies, including data classification, access controls, documentation and change management procedures. Work closely with business analysts, data scientists, and IT teams to ensure compliance, mitigate risk and deliver full-cycle data solutions.
• Mentor junior data specialists, analysts, and other engineers, and contribute to the firm’s best practices and technical standards.
• Be a key contributor and resource to the firm’s overall data strategy and architecture, including the development of best practices and procedures for developing and providing reports, dashboards and other data services throughout the firm.

Education and Work Experience Requirements:

• Bachelor’s or master’s degree in computer science, Information Systems, Data Engineering, or related field.
• 8+ years of hands-on experience in data warehouse development and optimization, ETL/ELT development, and reporting/BI solutions.
• Strong expertise in SQL (query optimization, stored procedures, indexing).
• Proficiency with Azure data lake/warehouse technologies (Azure Synapse, Azure Databricks, Microsoft Fabric, etc.).
• Experience with ETL tools (Informatica, Talend, SSIS, dbt, or similar).
• Strong background in BI/reporting tools (Power BI, SSRS, Looker).
• Solid understanding of data modeling (star schema, snowflake schema, OLAP/OLTP concepts).
• Knowledge of cloud platforms (Azure) and modern data stack tools.
• Strong problem-solving, analytical, and communication skills.