Work closely with software developers, data analysts, product managers, and business owners to optimize the data analytics lifecycle that impacts our colleagues and customers.
Work closely with data engineers to maintain and optimize our ingestion data pipelines.
Provide clean datasets to end users by designing, implementing, documenting, and optimizing our semantic layer: from raw data into foundational business data tables.
Own the quality, consistency, and readiness of reporting data tables to be exposed in our endpoints (e.g. Metabase and Lightdash)
Improve our company’s data literacy by educating product managers and business owners on how to use our business intelligence tools.
Apply software engineering best practices to our data transformation code (e.g. version control, testing, continuous integration).
Requirements & Skills:
3+ years of experience in building analytics in a SaaS B2B environment in at least one (more is a plus) of the following business areas: Product, Marketing, Sales, and Finance.
Strong proficiency in SQL and Python.
Experience with data warehousing (e.g. Snowflake) and ETL/ELT tools (e.g. dbt)
Experience with data modeling techniques (e.g. snowflake schema).
Experience with data visualization tools (e.g. Metabase, Looker, or Lightdash).
Experience working with a version control environment (e.g. git).
Experience implementing and maintaining data quality alerting and monitoring.
