Director of Data Operations

This is Remote.

This role owns the end-to-end delivery of data from multiple source systems to Business Intelligence consumers across the organization. The Director leads a team of data engineers and operations specialists responsible for automated ingestion pipelines, BI data delivery, system ownership, and on-call operations. The role carries equal weight in technical leadership and people management — the right candidate is as comfortable designing a pipeline architecture as running a team retrospective or briefing an executive on data

health.

Duties & Responsibilities

• Own the organization strategy around design, automation, and monitoring of all data ingestion pipelines from APIs, databases, flat files, SaaS platforms, and event streams to BI destinations
  
• Manage and improve systems and processes for Data Operations such as automated deployment, source code management, CI/CD and release management, etc.
  
• Working with data leadership, own the strategy and implementation of governance of data routing, access, and permissions for data products such as data warehouses and Power BI reports and semantic models
  
• Establish and enforce SLAs for data freshness and delivery, including partnership with other teams across the organization
  
• Maintain a system ownership register mapping every pipeline and platform to a named owner and backup with escalation paths and runbooks
  
• Design and manage support and incident response processes for all Tier 1 data systems
  
• Coach and develop a team of data engineers and operations analysts using structured 1:1s, sprint planning, and clear work prioritization to protect focused delivery time
  
• Identify system owners for every integration, ensure each owner can operate their system independently, and conduct quarterly ownership reviews
  
• Manage external vendor relationships: negotiate SLAs, lead POC evaluations, and ensure data sharing agreements comply with Legal and Compliance requirements
  
• Enforce documentation and change management standards across all production systems; track operational metrics and drive continuous improvement
  

Candidate Requirements

• Bachelor's degree in Computer Science, Information Systems, Data Engineering, or related field; or equivalent combination of education and experience. Fifteen (15) years of hands-on data platform experience required.
  
• Cloud or BI platform certifications (Microsoft Fabric, Power BI, Azure, Snowflake) are a plus.
  
• Fifteen (15) or more years in data engineering, data operations, or analytics engineering with significant hands-on pipeline design and delivery
  
• Eight (8) or more years in people management with direct reports, including performance management and career development
  
• Hands-on experience building automated ETL pipelines (Airflow, dbt, Fivetran, or equivalent)
  
• Proven experience ingesting data from diverse sources: REST APIs, relational databases, flat files, SaaS platforms, and streaming feeds
  
• Direct experience delivering data to Power BI or an equivalent enterprise BI platform including semantic model and dataflow ownership
  
• Advanced SQL; working proficiency in Python or PySpark for pipeline logic and automation
  
• Experience with cloud data warehouse or lakehouse platforms (GCP/BigQuery, Snowflake, Azure Synapse, Databricks, or equivalent – GCP a plus, but equivalent experience is fine)
  
• Understanding of dimensional modeling, star schema, and BI-optimized data design
  
• Experience establishing on-call rotations, incident severity frameworks, runbooks, and post-mortem practices for production data systems
  
• Demonstrated ability to build system ownership frameworks with named owners, escalation paths, and documented operational procedures
  

Skills & Competencies

• Systems thinker who sees the full data delivery chain and identifies gaps before they become incidents
  
• Coach who invests in helping team members do focused, high-impact work and grow their expertise
  
• Exceptional communicator — fluent in both technical deep-dives with engineers and plain-language briefings with executives
  
• Ownership mindset: treats pipelines as production systems with SLAs, not batch scripts, and holds the team to the same standard
  
• Servant leader who removes blockers and creates conditions for deep, high-quality work
  
• Collaborative across functions: builds genuine working relationships with BI Power Users, IT, Compliance, and external vendors