Tech PMO

Job Title: Technical Program Manager, Data Quality Engineering

Location: Pune

Key Responsibilities

As a Technical Program Manager, Data Quality Engineering, candidate will:

1. Technically Drive Data Automation Initiatives:

• Strategically define, design, and technically lead the implementation of end-to-end data automation solutions across our data pipelines and platforms.
• Identify opportunities for automation to enhance data ingestion, transformation, validation, and delivery processes, ensuring scalability, efficiency, and reliability.
• Collaborate closely with Data Engineers, Architects, and other stakeholders to integrate automation seamlessly into the existing data ecosystem.
• Evaluate and recommend new technologies, tools, and methodologies to advance our data automation capabilities.

1. Mentor and Coach for Data Quality Engineering Solutioning:

• Act as a primary technical mentor and coach to the Data Quality Engineering team, guiding them through complex data quality challenges and solution design.
• Provide expert guidance on best practices for data profiling, data validation, data cleansing, data reconciliation, and anomaly detection.
• Foster a culture of continuous learning, technical excellence, and shared ownership for data quality across the engineering organization.
• Lead technical deep-dives, design reviews, and problem-solving sessions to ensure robust and scalable data quality solutions.

1. Drive Automation Efforts for Data Quality Test Automation Tool:

• Lead the end-to-end automation efforts for our enterprise Data Quality Test Automation tool e.g., "Broadcom CA TDM", "Informatica Data Quality", or "custom frameworks"
• Define and implement automation pipelines for data quality test case creation, execution, reporting, and defect management.
• Develop strategies for integrating data quality gates into CI/CD pipelines to ensure data integrity throughout the software development lifecycle.
• Ensure optimal utilization of the data quality test automation tool, maximizing its effectiveness and efficiency.

1. Support Interviews and Related Delivery by Leveraging Strong Big Data Understanding:

• Actively participate in the recruitment process for Data Quality Engineers and other Big Data-focused roles.
• Conduct in-depth technical interviews, assessing candidates' proficiency in Big Data technologies (e.g., Apache Spark, Hadoop, Kafka, data warehousing, data lakes, Data pipelines).
• Contribute to building a high-performing, technically strong Data Quality Engineering team.
• Provide technical oversight and guidance on project delivery, ensuring architectural soundness and adherence to best practices.

1. Drive Team and Delivery Aspects of Data Quality Engineering:

• Own the overall delivery lifecycle for Data Quality Engineering initiatives, from conception to deployment and ongoing operations.
• Implement and champion Agile methodologies (Scrum/Kanban) to manage project timelines, sprints, and backlogs effectively.
• Manage stakeholder expectations, communicate project status, risks, and dependencies clearly and proactively.
• Ensure high-quality deliverables that meet business requirements and technical standards.
• Identify and mitigate risks, resolve impediments, and drive continuous improvement in team processes and performance.

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field.
• 8+ years of experience in software engineering, with at least 3+ years in a Technical Program Manager, Technical Lead, or Lead Data Engineer role focused on data quality or data platform initiatives.
• Deep technical understanding of the Big Data ecosystem
• Proven expertise in Data Quality concepts and methodologies: Data profiling, data validation, data cleansing, data reconciliation, anomaly detection, and data governance.
• Demonstrated experience in leading automation efforts for data quality testing, including designing and implementing test automation frameworks and integrating them into CI/CD pipelines.
• Strong understanding of software development lifecycle (SDLC) and Agile methodologies.
• Exceptional communication, interpersonal, and leadership skills, with the ability to influence, motivate, and mentor technical teams.
• Proven ability to manage multiple priorities, stakeholders, and complex projects in a dynamic environment.