Engineering Manager, Enterprise Data Platform

Morningstar Credit Ratings, LLC; Mumbai; On-site; INR 3,500,000 - 6,000,000; Full time

Job summary

Morningstar Credit Ratings, LLC in Mumbai seeks an experienced Data Engineering Lead to shape the data platform, mentor a growing team, and collaborate with technology and business leaders to set the roadmap.

You will drive scalable data pipelines on Snowflake, Airflow, Kafka, and cloud environments, advancing governance and compliance, while pushing AI-driven automation across data products.

Qualifications

• 8+ years in data engineering with leadership experience.
• Design and maintain large-scale cloud data architectures and pipelines.
• Proficient in SQL and Python for data manipulation and automation.
• Deep knowledge of ETL/ELT, Airflow, Kafka, and data governance.
• Experience with enterprise data sources (CRM/ERP/Marketing/Finance).
• Hands-on AI/ML experience for data products.
• Excellent communication and stakeholder management.

Responsibilities

• Lead, mentor, retain top talent and build a high-performing data engineering team.
• Define and drive the data engineering roadmap aligned with enterprise data strategy and business objectives.
• Collaborate with senior technology and business leaders to define data platform priorities, architecture, and long-term vision.
• Promote a culture of innovation, operational rigor, and customer empathy within the data organization.
• Oversee the design, development, and maintenance of high-quality data pipelines and ELT/ETL workflows across enterprise systems and PitchBook’s platform.
• Ensure scalable, secure, and reliable data architectures using modern cloud technologies (e.g., Snowflake, Airflow, Kafka, Docker).
• Lead AI learning initiatives and integrate AI/ML-driven solutions into data products to enhance automation, predictive insights, and decision intelligence.
• Champion data quality, governance, lineage, and compliance standards across the enterprise data ecosystem.
• Partner with engineering and infrastructure teams to optimize data storage, compute performance, and cost efficiency.
• Support career development through mentoring, skill-building, and performance feedback.

Skills

Leadership

SQL

Python

Data modeling

Communication

Stakeholder management

Cloud data architectures

AI/ML platforms

Team mentoring

Education

Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field

Tools

Snowflake

Airflow

Kafka

AWS

Azure

GCP

Docker

Job description

Primary Job Responsibilities

• Lead, mentor, retain top talent and develop a team of data engineers, fostering a culture of excellence, accountability, and continuous improvement
• Define and drive the data engineering roadmap aligned with enterprise data strategy and business objectives
• Collaborate with senior technology and business leaders to define data platform priorities, architecture, and long‑term vision
• Promote a culture of innovation, operational rigor, and customer empathy within the data organization
• Oversee the design, development, and maintenance of high‑quality data pipelines and ELT/ETL workflows across enterprise systems and PitchBook’s platform
• Ensure scalable, secure, and reliable data architectures using modern cloud technologies (e.g., Snowflake, Airflow, Kafka, Docker)
• Lead AI learning initiatives and integrate AI/ML‑driven solutions into data products to enhance automation, predictive insights, and decision intelligence
• Champion data quality, governance, lineage, and compliance standards across the enterprise data ecosystem
• Partner with engineering and infrastructure teams to optimize data storage, compute performance, and cost efficiency
• Support career development through mentoring, skill‑building, and performance feedback

Skills and Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field
• 8+ years of experience in data engineering or related roles, including at least 2–3 years of leadership experience managing technical teams
• Proven experience designing and maintaining large‑scale data architectures, pipelines, and data models in cloud environments (e.g., Snowflake, AWS, Azure, or GCP)
• Advanced proficiency in SQL and Python for data manipulation, transformation, and automation
• Deep understanding of ETL/ELT frameworks, data orchestration tools (e.g., Airflow), and distributed messaging systems (e.g., Kafka)
• Strong knowledge of data governance, quality, and compliance frameworks
• Experience working with enterprise data sources (CRM, ERP, Marketing Automation, Financial Systems, etc.) is preferred
• Hands‑on experience with AI/ML platforms, model deployment, or data‑driven automation is a strong plus
• Excellent communication and stakeholder management skills with the ability to translate complex data concepts into business value
• Demonstrated ability to build high‑performing teams and lead through change

Working Conditions

The job conditions for this position are in a standard office setting. Employees in this position use PC and phone on an on‑going basis throughout the day. Limited corporate travel may be required to remote offices or other business meetings and events.

US Applicants: Morningstar is an E‑Verify program participant.

Right to Work (English)

Right to Work (Spanish)

Morningstar is strongly committed to creating and preserving equal opportunity for all employees and applicants. We make all employment decisions—including recruitment, hiring, compensation, training, promotion, transfer, discipline, termination, and other personnel matters—without regard to race, color, ancestry, religion, sex, national origin, age, disability, protected veteran status, marital status, sexual orientation, genetic information, citizenship, gender identity and expression, parental status, or other legally protected characteristics or conduct.