Manager, Analytics Engineering

Gopuff’s engineering team is building solutions to dramatically change the way people purchase their daily goods. We provide the modern-day solution to meet customer’s immediate everyday needs with products ranging from snacks and ice cream to household goods and beer, at the click of a button.

As an Analytics Engineering Manager at Gopuff, you’ll be responsible for leading and developing a team of engineers aimed at building trusted sources of truth for how we measure and manage our business. You’ll be an integral part of developing our data modeling and analytics data product strategy, inherently helping implement scalable and extensible solutions that expedite Gopuff’s data-driven decision speed and quality. We’re looking for a visionary that is passionate about data being treated as both a first-class citizen and a strategic asset, as well as an individual that can help lead and develop a team of skilled engineers that are extremely passionate about making data actionable at an enterprise scale.

Our stack currently consists of stitch and various data engineering pipelines for extracting and loading, snowflake, dbt, and looker. If you have expertise in these tools, or an appetite to learn more about them—let’s chat!

Responsibilities

Own, evangelize, and refine our self-service analytics strategy, focused on building world-class data products (transformed, curated data via dbt + key enterprise-impacting dashboards & visualizations in Looker) that standardize how key executives and practitioners manage the health of our core business

Partner with product managers, data + software engineers, and business stakeholders to obtain a holistic understanding of each team’s data needs and translate them into infrastructure and tooling that enables a data-driven culture

Lead a team of analytics engineers in building a portfolio of enhanced, cutting-edge business intelligence capabilities that empower data analysts, scientists, go-to-market teams, and other data consumers

Ensure that as the company’s strategic imperatives and business demands change and evolve, financial impact, reach, quality, and time-to-market are consistently cared for and considered as Analytics Engineering is developing and executing on their backlog of feature requests

Minimum Qualifications

Bachelors in Engineering, Business, Information Systems, or other quantitative discipline

Experience in leading, developing, and mentoring data engineers, data analysts, and/or data scientists from discovery, backlog refinement & curation, to stakeholder prioritization, through to feature execution

6-8+ years of experience in related analytical, business information/intelligence systems, and/or data engineering fields

Expert SQL proficiency with proven competencies in designing well-architected data models, optimizing for query performance, and clearly documenting code

Experience and strong knowledge in data warehousing concepts, big data technologies, and analytics platforms. Redshift and/or Snowflake experience strongly preferred

Experience with implementing and/or owning enterprise BI tooling (Looker, Tableau, or similar visualization/dashboarding tool)

Experience working with DBT or similar analytics workflow tools, as well as git workflows

Excellent communication skills to work with stakeholders to translate business needs and ideas into tractable work items.

Top-notch organizational skills and ability to manage multiple projects in a fast-paced environment

Move fast, be a team player, always be learning, and give back

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