Role Description

We are seeking an experienced Manager for the Data Engineering team. This role reports to the Senior Director of Data Engineering. This is a hands-on, player and coach role. The Manager is expected to remain deeply involved in the design, implementation, and review of data pipelines and data models while also leading and developing a team of data engineers. Success in this role requires balancing technical execution with people leadership and delivery accountability.

The Manager will influence and implement the technical direction of the data platform by proposing improvements, evaluating tradeoffs, and operationalizing solutions aligned with architectural direction set by senior leadership.

Key Responsibilities

• Data Pipelines and ETL:
  • Design, build, and maintain scalable, high-availability data pipelines that ingest, transform, and serve structured and unstructured data across the enterprise.
  • Own the end-to-end ETL and ELT implementation in Snowflake, with strong hands-on expertise including data loading patterns, performance tuning, warehouse sizing, and cost optimization.
  • Partner with Analytics, Product, and ML Engineering teams to deliver clean, well-documented data models that accelerate business insights.
  • Evaluate and implement modern data stack tooling (for example dbt, Airflow, Spark) aligned to evolving organizational needs and standards.
  • Define and enforce SLAs for data freshness, quality, and availability across all critical data products.
• Data Modeling and Business Logic:
  • Develop and maintain robust, well-documented data models that accurately reflect business processes, entities, and rules.
  • Deeply understand the business context behind the data and instill this understanding across the engineering team.
  • Champion data correctness as a first-class engineering concern.
  • Collaborate closely with Analytics and Business stakeholders to translate business logic into reliable, reusable data models.
  • Establish modeling standards and conventions that promote consistency and reduce ambiguity across the data platform.
• Data Lifecycle, Migration and Validation:
  • Own the full lifecycle execution of data from ingestion and transformation through delivery and consumption.
  • Lead data migration efforts including planning, mapping, execution, and post-migration validation.
  • Design and enforce data validation frameworks that verify correctness during transport, transformation, and migration.
  • Conduct and oversee data analysis to investigate pipeline behavior and validate business logic.
  • Document data flows, lineage, and transformation logic to ensure full auditability.
• Technical Leadership, Architecture Influence and Operational Excellence:
  • Contribute to the architectural evolution of the data platform.
  • Establish engineering best practices including code review standards and incident response expectations.
  • Promote a data quality culture by implementing automated testing and validation frameworks.
• Team Leadership and Hiring:
  • Lead and manage the day-to-day operations of a team of data engineers.
  • Partner with the Senior Director on workforce planning and hiring.
  • Conduct regular 1:1s, performance reviews, and career development conversations.
  • Build a psychologically safe, collaborative team environment.
  • Mentor and coach engineers through hands-on technical leadership.
• Data Governance and Compliance:
  • Partner with the Senior Director, Legal, Security, and Compliance to implement a data governance framework.
  • Implement and enforce data retention policies and audit logging practices.
  • Support security audits and compliance reviews as a primary data engineering contributor.
  • Partner with Legal, Security, and Compliance teams to ensure data handling practices align with regulatory requirements.
• Execution, Delivery and Cross-functional Collaboration:
  • Translate the data engineering roadmap into concrete project plans.
  • Actively manage project timelines and coordinate cross-functional dependencies.
  • Serve as the primary day-to-day point of contact for cross-functional teams.
  • Escalate tradeoffs, risks, and prioritization conflicts with clear recommendations.

Qualifications

• 8+ years of experience in data engineering, with at least 3–4 years in a people management or engineering lead capacity.
• Proven track record of building and scaling data pipelines in a production, cloud-native environment.
• Deep expertise in ETL and ELT design patterns, data modeling, batch and streaming data processing, and distributed data systems.
• Strong proficiency in SQL and Python; experience with orchestration tools such as Apache Airflow or Prefect.
• Deep, hands-on expertise with Snowflake as a primary data warehousing platform.
• Demonstrated ability to build and own end-to-end data models that encode business logic.
• Demonstrated experience implementing or operationalizing a data governance program at meaningful scale.
• Experience with compliance frameworks (SOC 2, GDPR, CCPA) and collaborating with Legal and Security teams.
• Exceptional communication skills with the ability to influence across technical and non-technical audiences.
• Demonstrated ability to balance hands-on technical execution with coaching, delegation, and delivery accountability.

Preferred

• Experience with cloud infrastructure on AWS or Azure.
• Background in or exposure to ML Engineering or feature store pipelines.
• Experience in a high-growth technology company or similarly fast-paced environment.
• BS or MS in Computer Science, Engineering, or a related technical field (or equivalent practical experience).

Work at Home Requirements

• A quiet, distraction-free environment to work from.
• A secure internet connection with consistent speeds greater than 20 Mbps for downloads and greater than 10 Mbps for uploads is required.
• The workspace area accommodates all workstation equipment and related materials.
• Employment is contingent upon eligibility to work in the U.S., employment history verification, and a background check.

Company Description

Revecore is an equal opportunity employer that does not discriminate based on race, color, religion, sex or gender, gender identity or expression, sexual orientation, national origin, age, disability status, veteran status, genetic information, or any other legally protected status. We believe that a diverse workforce fosters innovation and creativity, enriches our culture, and enables us to better serve the needs of our clients and communities. We welcome and encourage individuals of all backgrounds, perspectives, and abilities to apply.

Must reside in the United States within one of the states listed below:

• Alabama
• Arkansas
• Florida
• Georgia
• Indiana
• Iowa
• Kansas
• Kentucky
• Louisiana
• Maine
• Massachusetts
• Michigan
• Minnesota
• Mississippi
• Missouri
• Nebraska
• New Hampshire
• North Carolina
• North Dakota
• Ohio
• Oklahoma
• Pennsylvania
• Rhode Island
• South Carolina
• South Dakota
• Tennessee
• Texas
• Vermont
• Virginia
• West Virginia
• Wisconsin