Job description
Our client is looking for a Senior Data Engineer to help build a solid and scalable data infrastructure and analytical environment. The ideal candidate enjoys data wrangling, optimizing data pipelines, and building solutions for data collections and analysis in parallelized and scaled out environments. The infrastructure currently processes billions of data points and hosts databases well into terabyte-size ranges, making this an interesting and challenging opportunity.
Terms: Direct Hire- Location: REMOTE or in-office (Downtown Denver)
- Rate: $150-175,000/year
Day to day:
- Build and extend data pipelines, written in Scala and running on Spark
- Tune Spark job performance
- Write clean, performant Scala code
- Work closely with our Product, Data Science and other Engineering teams to craft new products
- Contribute to Python and Scala-based microservices running on Kubernetes
Qualified candidates will likely have the following:
- 5 or more years of experience in a Data Engineer role
- BS/BA in Computer Science
- Experience developing cloud-based pipelines
- Strong experience with Spark
- Experience with Scala, and exposure to Python
- Experience with developing and deploying cloud-based data solutions
- Experience in any of the following is considered to be an asset: streaming technology such as Kafka or Google Pub/Sub, Databricks, AWS / GCP, Postgres, Protobuf, Snowflake or other Data Warehousing solutions, and Test-Driven Development
- Ability to operate with strong ownership and independence
What we are working with:
- Scala
- Python
- Spark
- Databricks
- AWS EMR, Athena, RDS (Postgres), Redshift, and S3
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