Director of Data operations, governance & Quality - Hybrid - MA - No C2C

We are looking for a director level candidate to fulfilll the needs for our growing Data services team in Andover, Ma. This is a true leadership role that requires a senior manager or director level talent that convert within 3 months to FTE and will be on site 4 days a week. 

This person is one of 2 senior leaders on our team reporting to the VP.  We expect a strong partnership with the other data services director who will be leading the other half of the team and roadmap. 

Overview:

Core Responsibilities of DataOps

• Platform Reliability & Performance

• Maintain and optimize data platforms (e.g., AWS, IDMC, Redshift, Snowflake).
• Ensure uptime, scalability, and performance of pipelines and infrastructure.

• Pipeline Orchestration & Automation

• Manage automated data workflows using tools like Informatica.
• Implement CI/CD for data deployments and configuration changes.

• Monitoring, Logging & Alerting

• Set up and maintain systems to monitor pipeline health, latency, failures, and anomalies.
• Proactively alert and respond to incidents to prevent data disruptions.

• Incident Response & Break/Fix

• Serve as the first line of defense for production issues.
• Troubleshoot and resolve platform, pipeline, or integration failures.

• DevOps for Data Engineering

• Support development teams with tooling, environment management, and deployment pipelines.
• Enable testing frameworks and version control for data assets.

• Security, Access, and Compliance Support

• Manage access controls, data encryption, and compliance logging.
• Partner with governance or security teams for audits and policy adherence.

Core Responsibilities of Governance & Quality

• Testing Framework & Automation

• Includes all non-prod and prod environments

• Establish a Data Quality COE
• Implement CDGC

• Metadata management, lineage, data catalog, data profiling and more

• Establish Governance

• Inclusive of compliance, security, audit, privacy

• Change Management

• Models, definitions, transformations

Measures for Success

• Enterprise data is accurate, trusted, and accessible to business stakeholders
• Data platform performance is stable, scalable, and proactively monitored
• Implementation of CI/CD and automation practices accelerate safe delivery of data products
• Implementation of a unified data catalog and metadata platform using CDGC which is actively used and maintained
• Establish governance policies and data quality practices are adopted across domains
• The team operates with high velocity and strong alignment across stakeholders