Manager, Engineering, Enterprise Data Platform

About the Role

Join the Enterprise Data Platform team as a Data Engineering Manager, leading a talented group of data engineers focused on constructing and refining robust data pipelines, managing expansive data models, and ensuring the availability, quality, and high performance of key enterprise data assets. This position blends hands-on technology expertise, strategic planning, and leadership skills to bolster data-informed decision-making and analytics.

Key Responsibilities

• Provide guidance, mentorship, and retention strategies to cultivate a high-performing data engineering team centered on excellence, accountability, and continual growth.
• Develop and maintain a data engineering roadmap aligned with organizational goals and enterprise data strategies.
• Collaborate with senior technology and business stakeholders to define platform priorities, architectural frameworks, and long-range visions.
• Foster a culture that values innovation, operational discipline, and customer-centric approaches within the data organization.
• Supervise the design, implementation, and maintenance of scalable, secure ELT/ETL pipelines across enterprise systems and platforms.
• Ensure architecture leverages modern cloud technologies such as Snowflake, Airflow, Kafka, and Docker to achieve security, scalability, and reliability.
• Lead initiatives integrating AI and machine learning into data services to improve automation, predictions, and decision support.
• Champion standards for data quality, governance, lineage, and compliance throughout the data ecosystem.
• Partner with infrastructure and engineering teams to optimize storage, computational efficiency, and cost-effectiveness.
• Support team members’ career progression through coaching, skill development, and constructive feedback.

Qualifications and Experience

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related disciplines.
• At least 8 years’ experience in data engineering or related fields, including 2–3 years of technical team leadership.
• Demonstrated expertise designing and managing large-volume data architectures and pipelines in cloud environments like Snowflake, AWS, Azure, or GCP.
• Advanced capabilities in SQL and Python for data transformation and automation tasks.
• Strong understanding of ETL/ELT processes, orchestration tools such as Airflow, and messaging platforms like Kafka.
• In-depth knowledge of data governance, quality assurance, and regulatory compliance standards.
• Experience working with enterprise-level data sources including CRM, ERP, marketing automation, and financial systems preferred.
• Hands-on familiarity with AI/ML platforms and deploying data-driven automation solutions considered a strong asset.
• Excellent communication and skills managing stakeholders, capable of translating intricate data concepts into business benefits.
• Proven success in building and leading effective teams through organizational change.

Working Environment

This position requires working in a typical office setting, with regular use of computers and telephones throughout the day. Occasional travel may be necessary for meetings or events at other locations.

Additional Information

Morningstar India is an equal opportunity employer committed to an inclusive and diverse workforce.