Sr Data Engineer

Company:
Location: La Jolla, CA 92037

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Senior Data Engineer

Synthetic Genomics, Inc. (SGI) is growing algae biofuels to one day power planes, propel ships and fuel trucks—ultimately offering the potential to cut emissions in half. SGI’s research spans from developing genetically engineered algae strains to cultivating acres of energy-rich algae at our state-of-the-art farm in California’s Imperial Valley. At the center of this research is SGI’s Integrated Data Platform, which is responsible for the automated collection and analysis of IoT sensor data and sophisticated laboratory measurements. SGI’s Integrated Data Platform provides a common operating picture that fosters cross team collaborations and provides an increased understanding of the factors driving performance variation across the scales from lab to farm.

To improve automation and reduce time to actionable insights, SGI is looking for a Senior Data Engineer to join its Integrated Data Platform team. We are looking for creative problem solvers with both a passion for innovation and a focus on delivering technical solutions. As a Senior Data Engineer, your work will improve the quality, reliability, accuracy and consistency of our research data. You will also work with the team to design, build and deploy data science and analytic solutions at scale.

Responsibilities

  • Design and develop ETL and data pipelines as well as validation tools using Python, SQL and AWS cloud technologies
  • Develop and maintain automated data availability, quality monitoring, and alerting solutions for the Integrated Data Platform
  • Design and implement data models, relational and dimensional
  • Use best practices for code development, optimization and unit testing
  • Partner with data scientists and laboratory scientists to define emerging requirements for the Integrated Data Platform, such as SLAs for data availability, quality, usability and correctness.

Qualifications

  • BS in Computer Science, Mathematics or similar field with a MS preferred
  • 7+ years of data engineering or software engineering experience
  • 3+ years of experience developing ETL and data pipelines
  • 3+ years of experience in data warehousing

Required Skills

  • Proficiency in Python and SQL
  • Ability to design and develop ETL and data pipelines from a variety of data sources (e.g., 3rd part application web APIs, databases, text files)
  • Experience working with MPP relational database (e.g., Amazon Redshift, Azure, Teradata)
  • Effectively communicate and collaborate with business and scientific leads from other organizations
  • Enjoys working with all aspects of data: analyzing, organizing, improving quality and efficient delivery

Preferred Skills

  • Ability to design and implement data models for a data warehouse
  • Experience working NoSQL and time-series databases
  • Experience using AWS technologies (RDS, Lambda, DynamoDB, AppSync, Kinesis, S3)
  • Knowledge of container management (Docker) and version control systems (Git)

Desired Skills

  • Database administration experience
  • Experience developing ETL pipelines that ultimately provide data and insights through BI Tools (e.g., Tableau, Qlik, Power BI)
  • Familiarity with Stream Processing systems
  • Familiarity with data science, statistics, and machine learning
  • Familiarity with database migration tools

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