Director- Engineering, Data Collection Technology (Navi Mumbai)
Morningstar is seeking a Director of Engineering to lead the Data Collections Technology team in Navi Mumbai. This role involves defining technical strategy and managing global teams to architect high-throughput, resilient data ingestion platforms. The incumbent will oversee core ETL/ELT infrastructure and collaborate with AI/ML teams to drive automation and scalability. It is a high-impact leadership position requiring extensive experience in distributed systems and cloud architecture.
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Experience
12+ years
Function
Engineering
Work mode
Onsite, India
Company
Tier 2
What you will work on
Morningstar is seeking a Director of Engineering to lead the Data Collections Technology team in Navi Mumbai. This role involves defining technical strategy and managing global teams to architect high-throughput, resilient data ingestion platforms. The incumbent will oversee core ETL/ELT infrastructure and collaborate with AI/ML teams to drive automation and scalability. It is a high-impact leadership position requiring extensive experience in distributed systems and cloud architecture.
TAL's take
Strong leadership role at an established global firm focused on high-scale data infrastructure.
Very clear responsibilities, scope, and technical requirements provided for a senior engineering leadership position.
Salaries at Morningstar
10.8 LPA average
Based on 23 Grapevine salary entries for Morningstar.
Engineering
2 - 4 years | L2
8 LPA average
Range: 8 - 9 LPA
Engineering
4 - 6 years | L1
9 LPA average
Range: 9 - 9 LPA
Engineering
6 - 8 years
20 LPA average
Range: 20 - 20 LPA
Engineering
10 - 12 years | L1
22 LPA average
Range: 22 - 22 LPA
Must haves
- 12+ years of experience in large-scale software engineering or platform architecture
- 7+ years leading technical teams
- Experience managing managers and geographically distributed teams
- Expertise in distributed systems architecture
- Expert-level knowledge of cloud-native architecture
- Proficiency in managing and optimizing large-scale ETL/ELT pipelines
Tools and skills
Nice to have: ai/ml, dataops, mlops.
About the company
Established global financial services and investment research firm with a substantial engineering footprint.
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