Senior Managing Consultant Data Engineer

Benefits and impact: Join Berkeley Research Group, LLC as a Senior Managing Consultant Data Engineer in New York, NY (onsite). This role is hands-on and delivery-focused, leading data engineering workstreams that support AI-enabled financial services solutions. You will build dependable data products with clear operating guidance, collaborate across AI and domain teams, and help translate client business and risk requirements into production-ready pipelines and controls.

Salary: USD 158,000 - 210,000 per year. Experience: minimum 5 years for this level.

Responsibilities

• Lead data engineering workstreams from discovery through production handover, managing technical dependencies, delivery risks, and implementation decisions with client business and technology teams.
• Design and build batch and streaming pipelines in Python and SQL to ingest, transform, and reconcile data from operational systems, APIs, files, and third-party sources.
• Develop ingestion processes for structured records and unstructured documents, including extraction, metadata capture, exception handling, and traceability to source material.
• Create warehouse and lakehouse data models for operational reporting, analytics, and AI use cases while preserving business definitions and reconciliation controls.
• Implement data quality checks, lineage, access controls, and PII handling in coordination with client security, privacy, and risk teams.
• Enable retrieval-ready data for AI applications through document parsing, chunking, metadata enrichment, embedding pipelines, and access-aware indexing alongside AI engineers.
• Work in the AI Co-lab with domain experts and vendor partners to frame data requirements, compare implementation options, and validate approaches using realistic financial services scenarios.
• Build automated tests, deployment pipelines, monitoring, and recovery procedures to make data products dependable and support client ownership.
• Mentor engineers and review code and designs, coordinating with AI, application, change, and risk colleagues to deliver integrated solutions and measure operational impact.
• Capture domain knowledge in reusable schemas, pipeline components, and implementation guides, and contribute technical estimates, assumptions, and data dependencies to proposals and next client pursuits.

Requirements

• Minimum 5 years of prior applicable work experience for Managing Consultant level; minimum 7 years for Sr. Managing Consultant level.
• Demonstrated senior, hands-on delivery of production data pipelines and data products, with practical experience recognized regardless of formal education or certification.
• Strong Python and SQL skills, including the ability to design, debug, optimize, and test ingestion and transformation processes across APIs, databases, files, and documents.
• Experience implementing warehouse or lakehouse models, and ability to explain choices related to schema design, storage, orchestration, incremental processing, and reconciliation using tools such as Spark, dbt, or comparable technologies.
• Applied data quality, lineage, least-privilege access, and sensitive-data controls in production, including translating business and risk requirements into testable engineering controls.
• Ability to prepare structured and unstructured data for AI retrieval, covering document parsing, chunking, metadata design, indexing, and preservation of source provenance and access permissions.
• Delivered maintainable data services using version control, automated testing, CI/CD, monitoring, and cloud infrastructure, and ability to diagnose reliability, performance, and cost issues.
• Ability to lead complex technical workstreams, mentor engineers, collaborate with client stakeholders, clarify requirements, communicate trade-offs, and contribute credible scope and effort estimates.
• Ability to travel to client sites as needed.

Technologies

• Python
• SQL
• Spark
• dbt
• CI/CD
• Snowflake

Preferred

• Industry experience building operational applications at a leading bank, lender, or financial services institution.
• Relevant financial services experience in consumer lending, commercial lending, or payments (mortgage, credit card, personal loan, auto lending; servicing, collections, and default are valuable). Adjacent banking or wealth and asset management experience is a plus.
• Experience building retrieval data foundations for production AI applications, including vector or hybrid search, document versioning, and evaluation of retrieval quality.
• Experience with change data capture, event-driven processing, or distributed data platforms across cloud and hybrid environments.
• Experience evaluating vendor data capabilities or converting domain expertise into reusable data assets, accelerators, and client implementation patterns.
• Experience implementing the Snowflake platform.

Required (Legal/Work Authorization)

Candidates must be able to verify their legal right to work in the United States without employer sponsorship now or in the future.