WHO ARE YOU?

• An experienced data engineer with demonstrated success in designing & maintaining data warehouses in Google BigQuery or other “big data” technologies
• A technology enthusiast who appreciates and understands the infrastructure their code runs on
• A results-oriented thinker who works backward from desired outcomes to best-practices
• A creative engineer who matches the complexity of a solution to the complexity of the problem
• A problem-solver who can quickly understand and correct problems with data pipelines
• An obsessive perfectionist who knows when to put down the paintbrush and ship

WHAT ARE YOUR RESPONSIBILITIES?

• Develop and maintain tools that bridge disparate data sources across the organization to serve data models, dashboards, decision aids, and business case analysis with up-to-date and accurate information.
• Collaborate with our data scientists on engineering predictive features from our product intelligence database.
• The prototype, implement and optimize data new pipelines and architectures that can transform our data to impactful insights.
• Create robust daily, weekly, or monthly automated processes to deliver impactful work.
• Create innovative and efficient techniques that better solve the problems we are working on
• Assess risks to proposed analytics solutions based on the quality of existing data sources and actively develop QA procedures to mitigate those risks.
• Tailor our syndicated data to retail and CPG business needs in a robust and scalable way.
• Facilitate knowledge transfer across the business between Product Delivery and Commercial teams.
• Recommend and implement enhancements that standardize and streamline processes, assure data quality and reliability, and reduce processing time to meet client expectations.

YOU ALREADY:

• Have a professional quantitative background with an education that stresses analytical thinking and quantitative methods (STEM)
• Have several years of experience as a data engineer with demonstrated success in designing & maintaining data warehouses
• Have a strong knowledge of Python & SQL in a data context (iterators, pandas, scikit-learn, etc.)
• Are passionate about innovating new ways to answer novel problems
• Are comfortable with being given the self-autonomy to work independently and experiment with new ideas and new ways to design and implement data science solutions to advance business goals
• Have confidence in being the expert on SPINS data capabilities and best practices based on independent synthesis of a broad range of data
• Familiarity with Docker and Google Cloud infrastructure is a plus