Geared toward mid-level data engineers comfortable with designing AI agents and optimizing cloud infrastructure costs, based in Gurugram for a hybrid work model.
Derived from job-description analysis by Serendipath's career intelligence engine.
Original posting from MongoDB
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 to speak to candidates who are 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
About MongoDB
MongoDB is built for change, empowering our customers and our people to innovate at the speed of the market. We have redefined the database for the AI era, enabling innovators to create, transform, and disrupt industries with software. MongoDB’s unified database platform, the most widely available, globally distributed database on the market, helps organizations modernize legacy workloads, embrace innovation, and unleash AI. Our cloud-native platform, MongoDB Atlas, is the only globally distributed, multi-cloud database and is available across AWS, Google Cloud, and Microsoft Azure.
With offices worldwide and over 60,000 customers, including 75% of the Fortune 100 and AI-native startups, relying on MongoDB for their most important applications, we’re powering the next era of software.
Our compass at MongoDB is our Leadership Commitment, guiding how and why we make decisions, show up for each other, and win. It’s what makes us MongoDB.
To drive the personal growth and business impact of our employees, we’re committed to developing a supportive and enriching culture for everyone. From employee affinity groups, to fertility assistance and a generous parental leave policy, we value our employees’ wellbeing and want to support them along every step of their professional and personal journeys. Learn more about what it’s like to work at MongoDB, and help us make an impact on the world!
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.
MongoDB is an equal opportunities employer.
Requisition ID
1273422593
Source: MongoDB careers