Responsibilities
- Architect and oversee implementation of a medallion architecture (Bronze/Silver/Gold) in Databricks
- Define and build Gold tables that serve as the canonical, business-ready data layer
- Eliminate ETL logic from DOMO, moving all transformation upstream into proper data pipelines (final-mile formatting excepted)
- Establish data modeling standards, naming conventions, and documentation practices that enable self-service consumption
- Lead a team of 4 data professionals including data engineers and analysts, with potential for growth
- Establish clear roles, career paths, and performance expectations
- Build a team culture centered on data quality, documentation, and serving business stakeholders
- Partner with HR on hiring decisions and team composition as the function scales
- Own the reliability and performance of all data pipelines and the Databricks platform
- Establish SLAs with business partners for data freshness, quality, and availability
- Create and track success metrics including pipeline reliability, Gold table coverage, data quality scores, and stakeholder satisfaction
- Implement data quality monitoring and alerting to catch issues before they impact downstream consumers
- Partner with Finance, Marketing, Supply Chain, and Operations to understand their data needs
- Translate business requirements into data models and pipeline specifications
- Enable self-service analytics by building intuitive, well-documented data products
- Serve as the data authority for the organization, establishing trust in a single source of truth
- Partner closely with the Director of Integrations to ensure seamless data flows from source systems into the data lake
- Coordinate with integration team on data delivery requirements and SLAs
- Support SAP S/4HANA migration by ensuring data architecture is ready for new source system patterns
- Collaborate with Security on data access controls, privacy requirements, and compliance
- Develop the multi-year data strategy and roadmap aligned with business priorities
- Build business cases for platform investments and team growth
- Stay current on data platform evolution and evaluate opportunities for capability enhancement
- Support international expansion with data architecture that accommodates regulatory requirements
Requirements
- 8+ years of experience in data engineering, analytics, or data platform roles, with at least 3 years in a management or leadership capacity
- Proven experience building foundational data infrastructure—you've taken an organization from fragmented data to a cohesive, trusted data platform
- Strong understanding of modern data architecture patterns including medallion architecture, data lakehouse concepts, and dimensional modeling
- Track record of partnering with business stakeholders to deliver data products that drive decisions
- Experience establishing data governance practices, quality standards, and documentation culture
- Strong executive communication skills with ability to articulate data strategy to non-technical audiences
- Deep familiarity with modern data platforms (Databricks strongly preferred; Snowflake, BigQuery, or similar acceptable)
- Understanding of data pipeline orchestration and ETL/ELT patterns
- Knowledge of SQL and data modeling best practices (star schema, slowly changing dimensions, etc.)
- Familiarity with BI platforms and their proper role in the data stack (consumption and visualization, not transformation)
- Understanding of data quality frameworks and monitoring approaches
Nice to Have
- Experience with DOMO or similar BI platforms
- Background in consumer packaged goods, retail, or e-commerce data
- Experience supporting ERP migrations from a data perspective
- Exposure to data governance tools and data cataloging
- Experience with PySpark or other distributed computing frameworks
