Responsibilities
Data Pipeline Architecture and Development: Design, build, and optimize robust and scalable data pipelines to process, transform, and integrate large volumes of data from various sources into our analytics platform.
Data Quality Assurance: Implement data validation, cleansing, and enrichment techniques to ensure high-quality and consistent data across the platform.
Performance Optimization: Identify performance bottlenecks and optimize data processing and storage mechanisms to enhance overall system performance and reduce latency.
Cloud Infrastructure: Work extensively with cloud-based technologies (GCP and AWS), to design and manage scalable data infrastructure.
Collaboration: Collaborate with cross-functional teams including Data Analysts, Data Scientists, Product Managers, and Software Engineers to understand requirements and deliver solutions that meet business needs.
Data Governance: Implement and enforce data governance practices, ensuring compliance with relevant regulations and best practices related to data privacy and security.
Monitoring and Maintenance: Monitor the health and performance of data pipelines, troubleshoot issues, and ensure high availability of data infrastructure.
Mentorship: Provide technical guidance and mentorship to junior data engineers, fostering a culture of learning and growth within the team.
Requirements
Strong hands-on Apache Spark experience — building and operating pipelines in production, not just familiarity
Proficiency in PySpark or Scala for Spark development
Proven track record delivering ETL pipelines and data integration at scale
Solid SQL skills and command of data modeling concepts
Cloud platform experience (AWS, GCP, or Azure) in a production data context
Comfortable working with distributed systems and big data formats (Parquet, Delta Lake)
Nice To Have
Experience with pipeline orchestration tools, particularly Apache Airflow
Exposure to the geospatial or location analytics domain
Familiarity with Hadoop ecosystem components
Background in both Python and Scala (beyond Spark context)
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 Placer.ai
Work with, and learn from, top-notch talent
Competitive salary
Excellent benefits
Noteworthy Links To Learn More About Placer
Placer.ai's $100M round C funding (unicorn valuation!)
See our data in action at The Anchor
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Placer.ai is committed to maintaining a drug-free workplace and promoting a safe, healthy working environment for all employees.
Placer.ai is an equal opportunity employer and has a global remote workforce. Placer.ai’s applicants are considered solely based on their qualifications, without regard to an applicant’s disability or need for accommodation. Any Placer.ai applicant who requires reasonable accommodations during the application process should contact Placer.ai’s Human Resources Department to make the need for an accommodation known.
May 2026
