Staff Data Engineer

MongoDB

Hybrid

Quick summary

Work type: Hybrid
Location: New York, NYGurgaon, India
Posted: 13 days ago
Nearby: 99+ roles within 25 mi

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Salary context

How this pay compares to similar roles

Similar $181k

$133k most similar roles pay here $229k

This listing doesn't post a salary. Most similar roles pay $147,325–$215,125.

Based on 240 similar postings.

Employer

About MongoDB

MongoDB is a leading American software company that develops and provides commercial support for a popular, source-available document database. Designed to handle unstructured and structured data natively, its platform is purpose-built for modern cloud applications, analytics, and AI experiences.

MongoDB currently has 287 open roles on FindRole.

Listed pay typically runs $126,500–$209,000 across 104 roles with salary data.

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At a glance

TL;DR · Staff Data Engineer

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As a Senior Data Engineer on the Data Engineering team at MongoDB, you will guide the development of highly performant ETL pipelines using Spark and other Big Data technologies to populate the Internal Data Platform. Your responsibilities include designing an architecture that supports robust medallion data structures, automating common tasks with AI agents, ensuring compliance with security regulations, and collaborating closely with sibling teams to enhance data scalability and accessibility. With over 10 years of experience in enterprise data lakes/warehouses, you will leverage your expertise in Spark, Python, AWS or GCP, and big data file types like Parquet and Avro to drive significant improvements in infrastructure cost savings and operational efficiency within a large-scale, high-performance environment.

Skills

Spark Python AWS GCP AI Hive Iceberg Glue Parquet Avro JSON MongoDB CI/CD

What you'll do

Guide the team in building high-performance ETL pipelines using Spark and Big Data technologies.
Design architecture for a robust medallion structure within the Internal Data Platform.
Lead initiatives to reduce infrastructure costs on Cloud hyperscalers through innovative solutions.
Develop AI agents to automate routine development and support tasks for efficiency gains.
Ensure datasets comply with security, compliance regulations, and have proper permissions set.
Collaborate with sibling teams to enhance data scalability, accessibility, and discoverability.

What we're looking for

10+ years of experience in enterprise data lakes/warehouses
Extensive hands-on experience with Spark and Python
Deep knowledge of AI, including codegen tools and agentic frameworks
Proficiency in AWS or GCP for cloud infrastructure management
Expertise in big data technologies like Hive, Iceberg, Glue, Parquet, Avro, JSON
Familiarity with real-time or streaming data technologies (preferred)
Leadership in designing scalable and secure internal data platforms

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