Big Data Team Lead

About
One of the fastest growing tech companies in North America, ("Placer") reached $100 million ARR "Centaur" status in 2024, within 6 years of launching the Placer platform. We previously crossed the $1B valuation "Unicorn" threshold in 2022.

Our A.I.-based SaaS platform transforms how leaders make critical decisions by unlocking unparalleled visibility into markets and locations, creating a blue ocean market of more than $100B. And the best part is, we accomplished this by leading a privacy-first business in which data has been stripped of user identifiers and only aggregated information is provided within the platform.

Our platform provides instant visibility into almost any location in the U.S. We have grown exponentially over the past 6 years, counting more than 4,000+ paying customers including many Fortune 500 companies, such as, JP Morgan Chase, Wayfair, Google and many more.

Named one of Forbes America's Best Startup Employers and a Deloitte Technology Fast company, we are proud of our collaborative, innovative and inclusive culture.

Summary
As a Big Data Team Lead at , you will lead a core team focused on the ingestion of big data and the development of core algorithms. Your role will involve building scalable and robust solutions for processing massive geospatial datasets, including spatially-focused algorithms. You will also be responsible for developing innovative big data solutions to ensure accuracy and efficiency within a fast-paced and evolving technical ecosystem. This position requires a passionate leader with a strong background in big data technologies and a drive to innovate.

Responsibilities

• Lead and manage a big data engineering team, focused on processing high-volume spatial-temporal data, while also engaging in hands-on technical tasks.
• Collaborate daily with product managers, R&D stakeholders, and data scientists to translate requirements into robust data systems.
• Prioritize and scope incoming feature requests and technical improvements to balance innovation with stability.
• Maintain and evolve the team's Apache Spark-based data pipelines, including optimization and scaling.
• Lead technical planning sessions, foster ownership and accountability within the team.
• Drive project-level KPIs and data quality KPIs such as pipeline completion time, job reliability, data freshness metrics and data accuracy.
• Manage 3–6 direct reports.

Requirements

• 2 years of experience in leading a data engineering team
• Strong expertise in Apache Spark, and big data pipeline design.
• Deep understanding of big data architecture in cloud environments, ideally GCP (e.g., Dataproc, BigQuery, GCS, Composer).
• Problem-solving mindset with the ability to diagnose complex system behavior and debug issues across layers of the stack.
• Experience with geospatial data or spatial analytics (Advantage).
• Familiarity with Airflow (Advantage) Proficiency in Scala (Advantage)
• Effective communicator with adaptability and prioritization skills to align cross-functional teams and balance short- and long-term goals.
• BSc in Computer Science, Engineering or a related technical field (or equivalent experience in the industry).

WHY JOIN PLACER.AI?

• Join a rocketship We are pioneers of a new market that we are creating
• Take a central and critical role at
• Work with, and learn from, top-notch talent
• Competitive salary
• Excellent benefits

Noteworthy Links To Learn More About Placer

• in a nutshell
• 's $100M round C funding (unicorn valuation)
• 's data
• in the news
• COVID-19 Economic Recovery Dashboard

is committed to maintaining a drug-free workplace and promoting a safe, healthy working environment for all employees.
is an equal opportunity employer and has a global remote workforce. 's applicants are considered solely based on their qualifications, without regard to an applicant's disability or need for accommodation. Any applicant who requires reasonable accommodations during the application process should contact 's Human Resources Department to make the need for an accommodation known.