Data Engg. Governance

Architect – Data Engineering Governance & Data Security
Experience: Minimum 7+ Years Overall Experience, with 5+ years in data engineering , 2+ Years in Data Engineering governance and 3+ years in data security
Department: DIA - Architecture Team
Role Summary
We are seeking an accomplished Architect – Data Engineering Governance & Security to join our team. This role will be instrumental in establishing and maintaining robust data engineering governance frameworks, ensuring best practices and standards are followed, and implementing advanced data security across the enterprise and self-service. You will be responsible for safeguarding data across its entire lifecycle, from ingestion and pipeline management to analytics and AI applications, while also ensuring compliance with regulatory standards.
Key Responsibilities
> Establish, enforce, and monitor Data Engineering governance standards, best practices, and guidelines across enterprise and self-service environments.
> Develop and maintain documentation for data engineering processes
> Define and implement data security policies and role-based access controls (RBAC/ABAC) across all data engineering processes.
> Oversee data classification, lifecycle management, and comprehensive metadata management to ensure transparency, traceability, and compliance.
> Implement and manage robust change control processes for all data engineering activities
Monitor, maintain, and optimize data pipelines and workflows, ensuring reliability, scalability, and efficiency.
> Continuously monitor and optimize the performance of data engineering processes and resource utilization.
> Promote a culture of data engineering governance, data security awareness, and operational excellence within the team and across the organization.
Proficiency:
Data Security
> Defining and implementing data security policies
> Security & role-based access control (RBAC/ABAC)
Data Engineering Governance
> Focuses on the practices and policies that ensure the effective management of data engineering processes:
> Establishing and enforcing governance standards, best practices, and guidelines
Data classification and lifecycle management
Documentation and Metadata Management
> Maintaining comprehensive documentation and metadata for data engineering processes to track data lineage, understand data transformations, and ensure transparency
Change Control Process
> Implementing and maintaining effective change control for data engineering activities
Performance Monitoring and Optimization
> Continuously monitoring and optimizing data engineering process performance and resource utilization
Data Pipeline Management
> Ensuring data pipelines are reliable, efficient, and scalable, including monitoring, maintenance, and workflow optimization
Technical Skills
Databricks Lakehouse Platform:
> Medallion Architecture
> Unity Catalog (data governance, lineage)
> Delta Lake & DLT Pipelines
> PySpark Workbooks
> Spark SQL & SQL Warehouse
Programming: Python, SQL, PySpark
AWS Cloud Services: IAM, S3, Lambda, EMR, Redshift, Bedrock
Other:
> Familiarity with DevOps and CI/CD processes
> Experience with any Data Security tool
Education
> Bachelor's or Master's degree in Computer Science, Information Systems, Data Engineering, or a related field (Master's preferred).
Preferred Qualifications
> Certifications in Databricks, AWS, or Data Security platforms.
> Experience working in regulated industries (e.g., finance, healthcare, manufacturing).
> Strong communication and documentation skills.
> Experience with dynamic data masking, data privacy, and compliance frameworks.

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