Analytics Engineer

Electric is the industry leader in providing world-class IT technology and real-time support for small and mid-sized businesses. With over 400 customers and more than 20,000 employee end-users, Electric’s IT platform includes: real-time support powered by 100+ IT technicians, security, device & inventory management, network & server management, application & cloud management, employee on-boarding and off-boarding, procurement & provisioning, and data monitoring & insights. Electric is a Series C company funded by an all-star team of investors including: Bessemer Venture Partners, GGV Capital, 01 Advisors, Primary Venture Partners, Bowery Capital, Slack, Atreides Management, Vintage Investment Partners, and Greenspring Associates.

Electric is now over 350 employees and led by a seasoned executive team. Our company is a fun, fast-paced environment with enormous opportunities for career advancement. We are seeking highly motivated, detail-oriented go-getters who want to move up in a tech startup.

Overview 

We are seeking a data analytics professional with a strong engineering profile to join our team. The person we hire into this role will work to apply software best practices to the problem of delivering timely, accurate, and flexible analytics solutions. The Analytics Engineer will also support and improve  our internal data platform. This will be a high impact role, with the potential to drive data-fueled productivity at a fast-paced product-oriented startup.

What you’ll do 

• Solve business problems by taking end-to-end ownership of data analytics projects, from data ingestion all the way through data modeling, visualization, and reporting.
• Follow engineering best practices such as testing, version control, code review, observability, and CI/CD to build highly reliable and extensible data products.
• Become a go-to expert and owner of tools up and down our data stack, including Snowflake,  dbt, Stitch, Pendo, and Looker.
• Build tools and processes to scale the delivery of high-quality analytical artifacts and insights in a rapidly changing environment.
• Perform code reviews, and mentor data analysts and other more junior team members on data engineering practices.

Who you are

• 3+ years of relevant work experience, including experience building and contributing to data analytics initiatives (data ingestion, warehousing, reporting, etc.).
• Working knowledge of Python, including experience working with the PyData stack, including Pandas for data manipulation and processing. 
• First hand experience operating and/or building solutions using job execution frameworks (e.g. Airflow, Dagster, Prefect) and MPP databases (e.g. Redshift, BigQuery, Snowflake).
• Capable of writing highly performant SQL in his or her sleep. Happens to have a favorite and least favorite business intelligence tool.
• Habitually pursues high test coverage and automation of rote tasks, with an eye toward driving up overall quality.
• Motivated to make the most of off-the-shelf tools and avoid writing custom ETL code -- but willing to do so in a pinch.
• Well organized and analytical by nature, with excellent collaboration and communication skills.
• Has at some point strongly considered reading a book by Ralph Kimball.

We are proud to foster a workplace free from discrimination. We strongly believe that diversity of experience, perspectives, and background will lead to a better environment for our employees and a better product for our users.