Principal Engineer - Data Pipeline

Work with the founding team to solve some of the hardest problems in heavy industry. We work with energy companies and utilities around the world to increase infrastructure reliability, reduce costs, and improve safety. Clients include Fortune 500 companies in North America and Europe.

Our current data pipeline is a collection of various AWS services including Kinesis, DynamoDB, Lambda, and S3, as well as custom Python. We are looking to hire a Principal Engineer to own defining and executing on our longer term streaming pipeline architecture to meet the needs of our growing customer base and data volumes. This is a high-impact role for ensuring the continued success of our data science and product engineering teams, enabling easy development and deployment of performant machine learning models and providing streaming insights to our customer platform.

Responsibilities:
  • Architect, build, and maintain a highly-available streaming data pipeline for high volumes of sensor data. We strongly encourage Principal Engineers to tinker with existing tools, and to stay up to date and test new technologies—all with the aim of ensuring that our existing systems don’t stagnate or deteriorate.
  • Actively partner with data science and the rest of product engineering to clearly define boundaries for and ownership of pipeline components.
  • Incrementally deliver pipeline milestones aligned with business goals. Iterate to improve performance and reliability.
  • Lead data pipeline team and assist with recruiting as we continue to grow.

Desired skills:
  • 7-10+ years of software engineering experience, including Java, Scala, Python, and/or C++
  • Solid problem solving, software design and architecture skills with a desire to mentor other engineers
  • Deep hands-on expertise with architecting, building, and maintaining a big data pipeline using tools such as Spark [Streaming], Flink, Hadoop, Storm, Apex.
  • Familiarity with relevant cloud services (Kinesis, SageMaker, EMR, Redshift, Azure ML Studio) and third-party providers (Databricks, Snowflake). Enjoys build vs. buy discussions to ensure focus remains on core values.

Bonus Points:
  • Experience with time series data and databases (InfluxDB, TimescaleDB, Kdb+)
  • Experience with ML/AI (extra bonus points for GPU computing)
  • Experience with regulatory compliance (PCI, GDPR, HIPAA, etc.) 

Benefits:
As a fast growing technology company, we offer all members of the team part-ownership through an Employee Stock Option Plan. We also offer health insurance benefits, discounted gym memberships, and encourage a team-oriented work environment with regular company outings.

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