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Senior Analytics Engineer (Remote)

Super.com LogoSuper.com
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Location

Remote

We are looking for a Senior Analytics Engineer to join our growing Data & Analytics team! As a Sr. Analytics Engineer at, you will evolve our foundational data infrastructure to support our expansion into new verticals. You will own the analytics infrastructure for these products end-to-end -- from data ingestion to reporting -- ensuring high data quality and availability for our core data sets. You will work with the business, engineering, and analytics teams to lay the foundation for effective reporting and analysis needed to scale up these ventures. As a senior member of the team, you’ll promote strong standards throughout the organization and help level-up team members through the adoption of software engineering best-practices.

Key Challenges

  • Data-Driven Culture: You will be an ambassador for our data-driven culture, taking data and shaping it to facilitate analysis, insight generation, and decision-making
  • Data Management: You will ingest, clean and organize raw data in a way that makes sense for both you and the team
  • Project Management: You will lead data projects from ingestion to reporting, showing your ability to manage scope and work with ambiguity
  • Collaborative Execution: You will liaise between Business, Engineering, and Data to translate business requirements into proper data capture and schema design
  • Data Strategy: You will help shape the data model at Super.com, which will advance our broader analytics strategy
  • Teamwork: You will coach data analysts and junior analytics engineers, helping them level-up technically and adopt software-engineering best practices

About You

  • 3+ years of work experience as an analytics engineer, data engineer, or full-stack data analyst
  • You are experienced in SQL, with an emphasis on writing performant code
  • You are a data modelling expert and have designed schemas before at previous organizations, ideally using DBT
  • You have a strong understanding of data warehouses and the modern data stack
  • You have a track record of delivering projects, including datasets that were used to drive key business decisions
  • You can self-serve by building ELT pipelines and reverse ETL pipelines using off-the-shelf tools, Airbyte connectors, or simple DAGs in Airflow leveraging Python
  • You have experience leveraging tools for data governance, data quality testing, and documentation
  • You can clearly communicate about technical subjects to non-technical people, and behave as a liaison between Business, Engineering, and Analytics

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