DataOps Engineer

📋 Description

• • Placer.ai is at the forefront of transforming how organizations comprehend and interact with the physical world. Our cutting-edge location analytics platform delivers unparalleled insights into locations, markets, and consumer behaviors, empowering thousands of clients, from Fortune 500 enterprises to local governments and non-profits, to make more informed, data-driven decisions. We pride ourselves on building the most advanced location intelligence platform available, while upholding an unwavering commitment to privacy. This demonstrates that powerful analytics and responsible data stewardship can, and must, coexist.
• • Our rapid growth is a testament to the market's demand for our solutions. In just six years since our launch, we achieved $100 million in Annual Recurring Revenue, attained unicorn status with a valuation exceeding $1 billion in 2022, and continue our trajectory as one of North America's fastest-growing technology companies. We are actively shaping a market opportunity projected to exceed $100 billion, and we are only just beginning this journey.
• • Recognized by Forbes as one of America's Best Startup Employers and by Deloitte as a Technology Fast 500 company, Placer.ai fosters a culture where innovation flourishes, collaboration is the standard, and every team member plays a crucial role in redefining how the world understands location.
• • We are seeking a highly skilled and motivated DataOps Engineer to take ownership of the critical infrastructure that underpins Placer's expansive, large-scale data processing platform. This is a unique, platform-centric role situated at the dynamic intersection of data engineering and infrastructure management. You will be the key individual responsible for ensuring that our Apache Spark workloads run reliably, efficiently, and at scale on Kubernetes, thereby enabling our data engineers to build and innovate with unwavering confidence.
• • You possess a deep understanding of data workloads, enabling you to make astute infrastructure decisions. Furthermore, you have the production-level instincts and experience necessary to maintain the health and performance of complex systems operating at scale. If the prospect of optimizing Spark job runtimes, fine-tuning cluster autoscalers for maximum efficiency, and developing internal tooling that makes a data platform feel truly effortless excites you, then this role is an exceptional fit.
• • Your primary responsibilities will encompass the design, deployment, and ongoing operation of the Kubernetes-based infrastructure that expertly manages Apache Spark and other large-scale data processing workloads. You will be accountable for the overall reliability, performance, and cost-efficiency of the data platform, including defining and meeting Service Level Agreements (SLAs), implementing sophisticated autoscaling strategies, managing resource quotas, and ensuring robust workload isolation.
• • You will meticulously manage Spark-on-Kubernetes configurations, maintain the Airflow infrastructure for workflow orchestration, and oversee Databricks integration, with a constant focus on tuning for optimal throughput, minimal latency, and controlled costs. A significant part of your role will involve building and maintaining robust CI/CD pipelines and implementing infrastructure-as-code principles for all data platform components, ensuring consistency, repeatability, and rapid deployment.
• • Developing advanced observability tooling is paramount. This includes establishing comprehensive metrics pipelines, implementing structured logging solutions, configuring effective alerting frameworks, and creating insightful data quality dashboards to proactively identify and address potential issues across the entire pipeline stack. You will foster close collaboration with our Data Engineering teams, gaining a deep understanding of their workload patterns and translating these insights into informed infrastructure decisions and enhancements.
• • You will manage critical cloud storage solutions, including Google Cloud Storage (GCS) or Amazon S3, and oversee the infrastructure for Delta Lake and Unity Catalog, ensuring data integrity and accessibility. Ultimately, you will drive platform improvements from conception through to deployment and sustained ownership, embodying a proactive and end-to-end approach to infrastructure management.
• • This role offers a unique opportunity to shape the foundational technology that powers Placer.ai's groundbreaking location intelligence platform, directly impacting our ability to deliver value to our customers and maintain our market leadership.