[Hiring] Data Quality / Data Governance Specialist @Encora

Role Description

We are seeking a highly skilled Data Quality / Data Governance Specialist with a strong focus on execution and implementation, not just documentation. This role is critical in ensuring data reliability, integrity, and governance across both batch and real-time data ecosystems. You will work closely with data engineering, analytics, and business teams to operationalize data governance frameworks, enforce data quality standards, and implement observability practices across modern data platforms.

Responsibilities and Duties

• Data Governance & Execution
  • Implement and operationalize data governance frameworks, policies, and standards across the organization.
  • Move beyond documentation to ensure real enforcement of governance practices within data pipelines and systems.
  • Define and enforce data contracts between producers and consumers.
  • Establish ownership, stewardship, and accountability models for data assets.
• Data Quality & Observability
  • Design and implement data quality frameworks to ensure accuracy, completeness, and consistency of data.
  • Define and monitor data quality rules and SLAs across datasets.
  • Implement and manage data observability tools to track data health, lineage, and anomalies.
  • Partner with engineering teams to integrate quality checks into pipelines.
• Data Architecture (Batch & Real-Time)
  • Ensure data quality and governance across batch processing architectures (e.g., Medallion architecture: Bronze, Silver, Gold layers).
  • Real-time/streaming systems.
  • Implement validation and quality checks across all layers of the data lifecycle.
  • Collaborate on architecture decisions to embed governance and quality by design.
• Modern Data Stack Implementation
  • Work hands-on with modern data technologies, including Python, SQL, Spark for data processing and validation.
  • AWS services such as Kinesis, Lambda, SQS/SNS.
  • Data lake/table formats such as Apache Iceberg.
  • Integrate governance and quality controls into data pipelines and workflows.
• Collaboration & Continuous Improvement
  • Collaborate with Data Engineers, Data Scientists, and Business stakeholders to ensure trusted data usage.
  • Educate teams on data governance best practices and standards.
  • Continuously identify opportunities to improve data reliability, reduce incidents, and increase trust in data.
  • Support incident resolution related to data quality issues and implement preventive measures.

Qualifications

• 5+ years of experience in Data Governance, Data Quality, or Data Engineering-related roles.
• Proven experience implementing (not just documenting) data governance frameworks.
• Strong hands-on experience with:
  • Data quality frameworks and validation strategies.
  • Data contracts and schema enforcement.
  • Data observability tools and practices.
• Experience working with:
  • Batch architectures (Medallion architecture preferred).
  • Real-time/streaming data pipelines.
• Proficiency in:
  • SQL and Python.
  • Distributed data processing tools such as Spark.
• Experience with modern data stack technologies:
  • AWS (Kinesis, Lambda, SQS/SNS).
  • Apache Iceberg or similar table formats.

Preferred Qualifications

• Experience with tools like Great Expectations, Monte Carlo, Databand, or similar observability platforms.
• Familiarity with data cataloging and lineage tools.
• Knowledge of data privacy, compliance, and regulatory frameworks.
• Experience with CI/CD integration for data pipelines.
• Strong understanding of data modeling and data architecture patterns.