Engineering Manager

Morningstar

8 - 13 years

40 - 45 Lacs

mumbai

Posted:-1 days ago| Platform:

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Skills Required

computer science erp automation architecture data quality stakeholder management analytics sql crm python

Work Mode

Work from Office

Job Type

Full Time

Job Description

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

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