High Salary: Architect – Data Engineering Governance

About Client:

Our Client is a multinational IT services and consulting company headquartered in USA, With revenues 19.7 Billion USD, with Global work force of 3,50,000 and Listed in NASDAQ, It is one of the leading IT services firms globally, known for its work in digital transformation, technology consulting, and business process outsourcing, Business Focus on Digital Engineering, Cloud Services, AI and Data Analytics, Enterprise Applications ( SAP, Oracle, Sales Force ), IT Infrastructure, Business Process Out Source. Major delivery centers in India, including cities like Chennai, Pune, Hyderabad, and Bengaluru. Offices in over 35 countries. India is a major operational hub, with as its U.S. headquarters.

- Job Title : Architect – Data Engineering Governance & Data Security
- Key Skills : Data Engineer, Data Security, AWS,
- Job Locations : PAN India
- Experience : 8+ Years.
- Education Qualification : Any Graduation.
- Work Mode : Remote.
- Employment Type : Contract.
- Notice Period : Immediate to 15 Days

Job Description:

Architect – Data Engineering Governance & Data Security

Location: [Specify: India / Remote / Other]

Experience: Minimum 8+ 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

Employment Type: Contract / Contract-to-hire

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.

---