Engineer, Big Data Engineering


  • Build complex ETL code
  • Build complex SQL queries using MongoDB, Oracle, SQL Server, MariaDB, MySQL Work on Data and Analytics Tools in the Cloud
  • Develop code using Python, Scala, R languages
  • Work with technologies such as Spark, Hadoop, Kafka, etc.
  • Build complex Data Engineering workflows
  • Create complex data solutions and build data pipelines
  • Create and manage data sources
  • Integrate with diverse APIs
  • Contribute to the ongoing development of the big data ecosystem
  • Work closely with stakeholders on the data demand side (finance, analysts, and data scientists)
  • Work closely with stakeholders on the data supply side (domain experts on source systems of the data)
  • Design and build optimized OLAP and Star Schema data structures
  • Build self-monitoring, robust, scalable batch and streaming data pipelines for 24/7 global operations.
  • Create highly reusable code modules and packages that can be leveraged across the data pipeline
  • Develop and maintain data dictionaries for governance of published data sources
  • Develop and improve continuous release and testing processes


  • Bachelor’s degree in computer science, computer engineering, or an engineering discipline •3+ years design & implementation experience with distributed applications
  • 2+ years of experience in database architectures and data pipeline development •Demonstrated knowledge of software development tools and methodologies
  • Presentation skills with a high degree of comfort speaking with executives, IT management, and developers
  • Excellent communication skills with an ability to right level conversations
  • Technical degree required; Computer Science or Math background desired
  • Demonstrated ability to adapt to new technologies and learn quickly


  • Highly analytical, motivated, decisive thought leader with solid critical thinking able to quickly connect technical and business dots
  • Has strong communication and organizational skills and has the ability to deal with ambiguity while juggling multiple priorities and projects at the same time
  • Able to understand statistical solutions and execute similar activities
  • Experience with big data tools such as Hadoop, Hive, Spark, etc, as well as knowledge of more traditional warehouses.
  • Experience delivering data pipelines and managing resulting data stores using managed cloud services (like AWS or Google Cloud Services)
  • Ability to identify and resolve performance and data quality issues
  • Experience with modern data pipelines, data streaming, and real time analytics using tools such as Apache Kafka, AWS kinesis, Spark Streaming, ElasticSearch, or similar tools.
  • Knowledge of machine learning tools and concepts a plus.

To apply, please email your cover letter and resume to