Analytics Engineer II

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 Engineer at Gopuff, you’ll be responsible for building and maintaining the bridge between our data and the rest of our organization. You’ll be helping ensure the integrity, reliability, and usability of productionalized data for all teams as they make critical data-driven decisions. This role sits within the Analytics Engineering team within our Engineering organization. You’ll have the opportunity to make a huge impact as the future success of Gopuff will largely depend on our ability to execute and scale operationally.

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

Be our go-to data expert and have a deep understanding of our data warehouse and data processing layers.

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

Own data integrity, availability, transformation logic, and efficient data access to support the growing needs of the organization.

Identify gaps in existing data, create data product specs, and work with Engineering teams to implement data tracking.

Incorporate automation wherever possible to improve data pipelines and analyses

Create testing and monitoring systems to ensure data quality and observability

Build and maintain documentation to ensure data accessibility to all stakeholders

Minimum Qualifications

Bachelor’s in Engineering, Business, Information Systems, or other quantitative discipline

2+ years of professional experience architecting and building data models that integrate complex and disparate data sources, using tools such as dbt

1+ years of professional experience building, maintaining reporting, and dashboards in various enterprise Business Intelligence platforms, such as Looker

Expert in SQL and database table design - able to write structured and efficient queries on large data sets

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

Experience working in 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

Preferred Qualifications

Master’s degree in Engineering, Business, Information Systems, or other quantitative discipline

Experience with ETL/ELT tools (bonus points for dbt!)

‌