Staff Data Engineer

MongoDB; Gurugram District; Hybrid; INR 4,000,000 - 10,000,000; Full time

Job summary

MongoDB’s Data Engineering team is seeking a senior data leader based in Gurgaon to architect and deliver scalable ETL pipelines for the Internal Data Platform, enabling fast analytics from massive enterprise data lakes and warehouses.

You will guide the team on Spark and Python, design the medallion architecture, optimize cloud costs, and build AI agents to automate development tasks, while coordinating with Security, Compliance, and Governance teams.

Qualifications

• 10+ years experience in enterprise data lakes/warehouses.
• 5+ years Spark and Python experience.
• 5+ years hands-on experience with AWS or GCP.
• Strong AI knowledge, including codegen tooling and agentic frameworks.
• Experience with big data table technologies (Hive/Iceberg/Glue).
• Familiarity with Parquet, Avro and JSON formats.
• Exposure to real-time or streaming data is a plus.

Responsibilities

• Guide Data Engineering on building high-performance ETL pipelines using Spark and other Big Data tech.
• Help design the architecture of Internal Data Platform to support robust medallion architecture.
• Provide thought leadership on infrastructure cost savings on cloud hyperscalers.
• Design and build AI agents to automate common development and support tasks.
• Collaborate with Security and Compliance to ensure proper data permissions and regulations.
• Coordinate with Data Platform and Governance teams to keep data scalable and discoverable.

Skills

Spark

Python

AWS

GCP

AI knowledge

Streaming data

Tools

Hive

Iceberg

Glue

Job description

The Data Engineering team is responsible for building ETL pipelines that populate the Internal Data Platform, which drives analytics that help the company run more efficiently. Our team builds highly performant and scalable processes that extract massive datasets and makes those datasets available for querying in an optimal way.

We are looking for candidates based in Gurgaon for our hybrid working model.

What you’ll do

• Guide the Data Engineering team on building highly performance ETL pipelines using Spark and other Big Data technologies
• Help design the architecture of our Internal Data Platform to support the implementation of a robust medallion architecture
• Provide thought leadership on ways to achieve infrastructure cost savings on Cloud hyperscalers
• Design and build AI agents that can help automate many of the common development and support tasks that the team performs
• Work with Security and Compliance teams to ensure that datasets have appropriate permissions and regulations in place
• Work with our Data Platform and Governance sibling teams to make data scalable, consumable, and discoverable

We’re looking for someone with

• 10+ years experience working on enterprise data lakes/warehouses
• 5+ years of Spark and Python experience
• 5+ years of direct hands‑on experience working with AWS or GCP
• Thorough AI knowledge, particularly with codegen tools and agentic frameworks
• Hive, Iceberg, Glue, or other technologies that expose big data as tables
• Familiarity with different big data file types such as Parquet, Avro, and JSON
• Exposure to real‑time or streaming data technologies is a plus

Success Measures

• In 3 months, you'll have a thorough understanding of the architecture of MongoDB’s internal Data and AI ecosystem
• In 6 months, you'll have owned the delivery of a large project from start (scoping, design) to finish (delivery)
• In 12 months, you'll have designed new features, led development work, and become a go‑to expert on parts of the system

MongoDB is an equal opportunities employer.

MongoDB is committed to providing any necessary accommodations for individuals with disabilities within our application and interview process. To request an accommodation due to a disability, please inform your recruiter.