Senior Managing Consultant – Data Engineer, Financial Services Operations & Technology

Berkeley Research Group (BRG)

. Lead data engineering workstreams from discovery through production handover .

Posted 10/23/2026full-timeUnited StatesSenior💰 $158,000 - $210,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and implementing data pipelines and models, with strong proficiency in Python and SQL. Capable of leading complex technical workstreams while ensuring data quality, security, and compliance in various operational contexts.

Highest-signal resume keywords

Python ProgrammingSQL ProficiencyData Pipeline DevelopmentData Quality ImplementationWarehouse and Lakehouse Design

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data IngestionData TransformationSchema DesignAutomated TestingMonitoring and Recovery ProceduresDocument ParsingMetadata DesignVersion ControlChange Data CaptureEvent-Driven Processing

Soft Skills

Mentoring EngineersCollaboration with StakeholdersCommunication of Trade-OffsLeadership of Technical Workstreams

Tools & Technologies

SparkDbtSnowflakeCI/CDCloud Infrastructure

Industry Keywords

Financial ServicesConsumer LendingCommercial LendingPaymentsMortgageCredit CardPersonal LoanAuto LendingWealth ManagementAsset Management

Tech Stack

Tools & technologies

CloudPythonSparkSQL

About the role

Key responsibilities & impact

Lead data engineering workstreams from discovery through production handover
Manage technical dependencies, delivery risks, and implementation decisions with client business and technology teams
Design and build batch and streaming pipelines in Python and SQL
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 source traceability
Design warehouse and lakehouse data models for operational reporting, analytics, and AI use cases
Implement data quality checks, lineage, access controls, and PII handling with security, privacy, and risk teams
Prepare retrieval-ready data through document parsing, chunking, metadata enrichment, embedding pipelines, and access-aware indexing
Work with domain experts and vendor partners in the AI Co-lab to frame data requirements, compare implementation options, and validate reusable approaches
Build automated tests, deployment pipelines, monitoring, and recovery procedures
Mentor engineers and review code and designs
Coordinate 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
Contribute technical estimates, assumptions, and data dependencies to proposals and client pursuits

Requirements

What you’ll need

Minimum 5 years of applicable work experience for Managing Consultant level
Minimum 7 years of experience for Senior Managing Consultant level
Senior, hands-on delivery of production data pipelines and data products
Equivalent practical experience recognized regardless of formal education or certification
Strong Python and SQL skills
Experience designing, debugging, optimizing, and testing ingestion and transformation processes across APIs, databases, files, and documents
Experience implementing warehouse or lakehouse models, including schema design, storage, orchestration, incremental processing, and reconciliation
Experience with technologies such as Spark, dbt, or comparable tools
Production experience with data quality, lineage, least-privilege access, and sensitive-data controls
Experience preparing structured and unstructured data for AI retrieval, including document parsing, chunking, metadata design, indexing, source provenance, and access permissions
Experience with version control, automated testing, CI/CD, monitoring, and cloud infrastructure
Ability to diagnose reliability, performance, and cost issues
Ability to lead complex technical workstreams, mentor engineers, collaborate with client stakeholders, communicate trade-offs, and provide scope and effort estimates
Ability to travel to client sites as needed
Preferred: experience at a leading bank, lender, or financial services institution
Preferred: relevant financial services experience in consumer lending, commercial lending, payments, mortgage, credit card, personal loan, auto lending, servicing, collections, default, banking, wealth management, or asset management
Preferred: experience building retrieval data foundations for production AI applications, including vector or hybrid search, document versioning, and retrieval-quality evaluation
Preferred: experience with change data capture, event-driven processing, or distributed data platforms across cloud and hybrid environments
Preferred: experience evaluating vendor data capabilities or converting domain expertise into reusable data assets, accelerators, and client implementation patterns
Preferred: experience implementing the Snowflake platform
Must be able to verify legal right to work in the United States without employer sponsorship now or in the future

Benefits

Comp & perks

Equal Opportunity Employer
Opportunity to build a new practice within an established consulting firm
Ability to work with the AI Co-lab, vendor partners, domain experts, and client teams
Professional mentoring and collaboration opportunities
Opportunity to contribute to recruiting, new offerings, thought leadership, and delivery improvement