Senior Analytics Engineer

Meet GTV

Grocery TV is the leading in-store retail media platform. Over 120 retailers partner with Grocery TV to modernize their stores and drive incremental revenue, while upholding a high-quality shopper experience. Grocery TV handles the complexities of operating an in-store media network so retailers can focus on what they do best—serving their customers. Reaching 1 in 4 Americans across nearly 6,000 stores, Grocery TV connects brands with real shoppers where nearly 90% of purchases take place. For more information, visit www.grocerytv.com.

Here are the problems you’ll be solving

Grocery TV is hiring a full-stack Analytics Engineer to strengthen our data foundation and deliver high-quality insights across the business. This role will focus primarily on our Retail vertical, supporting the data and reporting needs of Retail Sales, Retail Operations, and Device Engineering teams. You’ll also play a cross-functional role in helping maintain and improve data infrastructure and analytics across other business areas including Finance, Marketing, and Product.

We’re looking for someone who thrives on transforming messy, complex data into clean, trusted, and actionable systems. You’ll own data models, implement rigorous testing, design dashboards and reports, and partner with stakeholders to streamline workflows and enable decision-making. As a key member of our growing Data Platform team, you’ll help shape the future of our semantic layer and define scalable approaches to data quality and governance.

Responsibilities

• Design data infrastructure: Design and maintain data models, pipelines, and reporting systems that support network performance, sales enablement, operational health, and device reliability.
• Drive actionable insights: Work closely with cross-functional teams to understand their business context and success metrics. Translate those needs into datasets, dashboards, and tools that inform day-to-day decision-making.
• Ensure data quality and governance: Build and maintain robust testing frameworks, enforce standardized definitions, and maintain documentation that promotes trust and discoverability across the org.
• Shape our semantic layer: Play a key role in refactoring our semantic layer to support scalable, intuitive reporting and reduce friction for downstream data consumers.
• Foster collaboration and continuous learning: Collaborate across functions to solve data-intensive challenges, share knowledge, and contribute to the team's growth and adherence to best practices in analytics engineering.

Growth opportunities

• End-to-end ownership: Be the primary Analytics Engineer for our entire Retail vertical, from designing the data models to delivering dashboards that drive critical decisions.
• Shape our next-gen stack: Play a key role in the refactor of our semantic layer and data governance framework, a rare opportunity to help define foundational systems that will scale with the business.
• Varied, impactful work: Operate across the full analytics engineering stack - modeling, orchestration, scripting, visualization - while collaborating directly with stakeholders who rely on your work every day.
• Cross-vertical exposure: While Retail is your home base, you’ll contribute to data initiatives in other areas like Media, Marketing, and Product giving you a broad view of the business.
• Hone your craft: Work alongside a tight-knit team of experienced analytics and data engineers, and attend industry events (like dbt Coalesce) to stay on the cutting edge.

Qualifications

Must-Haves

• Technical Proficiency: Expert in SQL, data modeling, and BI reporting; advanced in Python, ETL/ELT workflows, and data warehouse technologies (e.g., Redshift, Snowflake).
• Tooling Familiarity: Experience with dbt, Airflow, and one or more BI tools (e.g., Looker, Tableau, Power BI).
• Data Quality & Governance: Track record of building tested, documented, and trusted data models and metrics that scale.
• Cross-functional collaboration: Strong communication skills and business acumen. Ability to gather requirements, translate ambiguous needs into technical solutions, and deliver insights that drive action.
• 4+ ye