Data Engineer (Consulting / Enterprise Financial Services)
Location: 100% Remote (US-based – EST Hours)
Engagement Type: Long-Term Contract (1+ Years, W2)
Compensation: $60.00 – $65.00/hr W2
Work Authorization: US Citizens or Green Card holders only (W2 requirement)
Overview
We are seeking an experienced Data Engineer to join a leading global professional services and consulting advisory practice, supporting a high-profile enterprise banking and financial services client.
In this role, you will drive a major enterprise-wide data modernization initiative aimed at breaking down scattered, siloed data repositories and transforming them into accessible, high-quality, and unified data assets across the organization.
Key Responsibilities
Develop and maintain scalable data pipelines using Python and advanced SQL.
Integrate, process, and validate large-scale datasets (handling volumes exceeding 1B+ records).
Implement and enforce data governance, data quality management, and automated reconciliation frameworks.
Participate in and conduct rigorous code reviews to maintain high coding and architectural standards.
Collaborate with cross-functional technical teams and client stakeholders to make data accessible, reliable, and usable firm-wide.
Required Qualifications
Core Technical Skills: Strong hands-on proficiency with Python and SQL for data engineering, pipeline development, and transformation.
Large-Scale Data Experience: Proven track record integrating and validating massive datasets (1B+ records).
Data Quality & Governance: Deep understanding of data quality frameworks, lineage, metadata, and governance best practices.
Engineering Best Practices: Experience conducting code reviews, version control (Git), and standard CI/CD practices.
Strongly Preferred
Hands-on experience with modern cloud data platforms: Databricks and/or Snowflake.
Exposure to building or supporting data visualization / reporting layers (e.g., Tableau, Power BI, or QuickSight).
Prior experience in financial services, banking, or enterprise consulting environments.