Senior Analytics Engineer

Meet GTV

We're modernizing in-store marketing to help brands and retailers reach shoppers. Our platform makes it easy to run digital advertising campaigns throughout the physical grocery store.

Our team enjoys the complexities of a product that's both physical and digital and balances the needs of retailers, brands, and agencies. We're founder-led with Series B funding and values that prioritize ownership, growth, transparency, and partnership.

Here are the problems you'll be solving

The media-focused Analytics Engineer will transform complex media data into clean, actionable insights, empowering the success of Grocery TV's advertising platform. They will design and maintain robust data infrastructure, create tools for media sales and operations, and enhance audience targeting while ensuring impeccable data quality. Collaborating closely with Media Sales, Ad Ops, and Marketing teams, they will streamline workflows, optimize programmatic performance, and drive data-informed decision-making across the media vertical.

Responsibilities

• Design and maintain robust data infrastructure : Build and optimize scalable data pipelines, models, and integrations using dbt, Looker, and Python to ensure accurate and timely delivery of media analytics and reporting.
• Drive actionable insights : Partner with Media Sales, Ad Ops, and Marketing to translate business needs into clear, actionable datasets, visualizations, and reports that inform strategic decisions.
• Ensure data quality and governance : Implement and enforce standards for media metrics, conduct rigorous quality checks, and maintain thorough documentation to ensure trust in media-related data assets.
• Develop tools to empower media sales and operations : Automate and streamline data-intensive workflows like audience targeting, campaign delivery, and sales planning.
• 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

Qualifications

Must-Haves

Nice-to-Haves

Compensation

As a part of our commitment to transparency, we use a market-based formula that provides consistency across roles & experience levels and publish all of our compensation data internally for our team. We're open to a range of experience levels for this position. Here are the annual salaries for each level :

In our initial conversation, we'll discuss what level best aligns with your experience.

Interview Flow

1. Apply

Apply and look for a response from our team about the next steps.

2. Intro interview with people team

Our recruiter will give you a call to learn more about you and answer any questions you might have about our team or the role.

3. Technical Interview with hiring manager

This will be a high-level conversation with your future manager. You'll meet with them to dive into the details of the position and your experience.

4. Technical interview with the hiring team

We'll dive deeper into your technical abilities by meeting with your future teammates and completing a collaborative technical assessment.

5. Values interview with collaborative teams

Chat with two people who work collaboratively with your role to give us a clear idea of how you'll work with others.

6. Leadership interview

Last but not least, you'll meet with one of our co-founders to make sure your values and career goals align well with our team.

Benefits and Perks

Our environment prioritizes collaboration, respect, and partnership. One of the ways we show that to our team is through our benefits program.

Ready to start?

To connect with our team, complete our quick application, and we'll be in touch soon.

Feeling imposter syndrome? Reach out to us!

We're happy to help you better understand the role and what we're looking for.

Salary : $167,000