MongoDB is the leading modern, general purpose database platform, designed to unleash the power of software and data for developers and the applications they build.
Developers around the world are using MongoDB to build software to create new businesses, modernize existing businesses, and transform the lives of millions of people around the world.
Headquartered in New York, with offices across North America, Europe, and Asia-Pacific, MongoDB has more than 15,000 customers, which include some of the largest and most sophisticated businesses in nearly every vertical industry, in over 100 countries.
MongoDB is growing rapidly and seeking a Data Engineer to be a key contributor to the overall internal data platform at MongoDB.
You will build data driven solutions to help drive MongoDB's growth as a product and as a company. You will take on complex data-related problems using very diverse data sets.
Our ideal candidate has experience with
several programming languages (Python, Scala, Java, etc.)
data processing frameworks like Spark
streaming data processing frameworks like Kafka, KSQ, and Spark Streaming
a diverse set of databases like MongoDB, Cassandra, Redshift, Postgres, etc.
different storage format like Parquet, Avro, Arrow, and JSON
AWS services such as EMR, Lambda, S3, Athena, Glue, IAM, RDS, etc.
orchestration tools such as Airflow, Luiji, Azkaban, Cask, etc.
Git and Github
CI / CD Pipelines
You might be an especially great fit if you
Enjoy wrangling huge amounts of data and exploring new data sets
Value code simplicity and performance
Obsess over data : everything needs to be accounted for and be thoroughly tested
Plan effective data storage, security, sharing and publishing within an organization
Constantly thinking of ways to squeeze better performance out of data pipelines
Nice to haves
You are deeply familiar with Spark and / or Hive
You have expert experience with Airflow
You understand the differences between different storage formats like Parquet, Avro, Arrow, and JSON
You understand the tradeoffs between different schema designs like normalization vs. denormalization
In addition to data pipelines, you’re also quite good with Kubernetes, Drone, and Terraform
You’ve built an end-to-end production-grade data solution that runs on AWS
You have experience building machine learning pipelines using tools likeSparkML, Tensorflow, Scikit-Learn, etc.
As a Data Engineer, you will :
Build large-scale batch and real-time data pipelines with data processing frameworks like Spark on AWS
Help drive best practices in continuous integration and delivery
Help drive optimization, testing, and tooling to improve data quality
Collaborate with other software engineers, machine learning experts, and stakeholders, taking learning and leadership opportunities that will arise every single day
MongoDB is an equal opportunities employer*