Software Engineer 3

MongoDB

Hybrid

Quick summary

Work type: Hybrid
Location: Gurgaon, India
Posted: 13 days ago
Nearby: 31 roles within 25 mi

Market check

Salary context

How this pay compares to similar roles

Similar $164k

$116k most similar roles pay here $207k

This listing doesn't post a salary. Most similar roles pay $136,400–$192,050.

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.

Most-posted roles

View all roles at MongoDB

At a glance

TL;DR · Software Engineer 3

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As a Senior Data Engineer on the Data Pipelines Engineering team at MongoDB in Gurgaon, India, you will design and maintain efficient ETL/ELT pipelines using Python and Spark to extract, transform, and load massive datasets into the company’s Internal Data Platform. Your daily tasks include ensuring data quality and reliability by following best practices, modeling large datasets with modern file formats like Parquet and Iceberg, and deploying pipelines on AWS and GCP cloud infrastructures. You will collaborate closely with Data Analysts and Scientists to deliver critical datasets for their projects while adhering to security and compliance standards. This role requires 4+ years of experience in building ETL pipelines, expertise in Python, Spark, SQL, and Airflow, familiarity with data warehousing concepts, and a background in cloud-based data platforms.

Skills

Python Spark SQL Airflow AWS GCP Hive Iceberg Glue Parquet Avro JSON CI/CD

What you'll do

Design and maintain efficient ETL/ELT pipelines using Python and Spark.
Ensure data quality and reliability across all pipelines following best practices.
Model large datasets using modern file formats like Parquet, JSON, Avro.
Deploy data pipelines on cloud infrastructure, primarily AWS and GCP.
Partner with Data Analysts and Scientists to deliver necessary datasets.
Work with Security teams to ensure proper permissions for datasets.

What we're looking for

4+ years experience building ETL pipelines for Data Lakes/Warehouses.
Expertise in Python, Spark, SQL, and Apache Airflow.
Proficiency in data warehousing concepts, analytical modeling, and quality validation.
Experience with modern file formats (Parquet, JSON) and table formats (Iceberg, Hive).
Background in building scalable data platforms on AWS or GCP.
Familiarity with real-time or streaming data technologies beneficial.

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