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Salary: USD 160,000 - 200,000 / annual
People Data Labs is a B2B SaaS company providing people and company data to leading organizations worldwide. The company integrates thousands of compliantly sourced datasets into a single, developer-friendly platform used by recruiting platforms, AI models, and custom audience creation tools.
As a Senior Software Engineer on the Data Engineering & Acquisition Team, you will architect and improve the data acquisition and processing platform, focusing on reliability, throughput, and observability. Key responsibilities include:
• Contribute to the architecture and continuous improvement of the data acquisition and processing platform
• Use and develop web crawling technologies to capture and catalog internet data
• Build, operate, and evolve large-scale distributed systems that collect, process, and deliver data from across the web
• Design and develop backend services managing distributed job orchestration, data pipelines, and large-scale asynchronous workloads
• Structure and model captured data, ensuring high quality and consistency across datasets
• Improve the speed, scalability, and fault-tolerance of ingestion systems
• Partner with data product and engineering teams to design and implement new data products
• Learn domain-specific knowledge in web crawling and data acquisition with mentorship from experienced teammates
Required qualifications include 7+ years of professional experience building or operating backend or infrastructure systems at scale. You should have solid programming experience in Python, Go, Rust, or similar languages with async/await and concurrency frameworks. Strong grasp of software architecture, backend fundamentals, concurrency, scalability, and fault tolerance is essential. You need solid understanding of browser rendering pipelines, web application architecture (auth, cookies, HTTP), network architecture and debugging (HTTP, DNS, proxies), and distributed systems concepts.
Additional requirements: experience designing or maintaining resilient data ingestion, API integration, or ETL systems; proficiency with Linux/Unix command-line tools; familiarity with message queues, orchestration, and distributed task systems (Kafka, SQS, Airflow); and experience evaluating and monitoring data quality.
Ideal candidates work independently in fast-paced, remote-first environments, communicate clearly in writing, write technical design documents, scope complex projects into deliverable milestones, and balance pragmatism with craftsmanship. Nice-to-haves include degrees in quantitative fields, red teaming experience, large-scale data ingestion experience, Apache Spark/Databricks proficiency, streaming data systems experience, SQL and data warehousing knowledge, cloud platform experience (AWS preferred), and modern data storage pattern understanding.
Compensation: $160K–$200K annually. Benefits include stock options, competitive salary, unlimited paid time off, medical/dental/vision insurance, health and fitness stipends, and permanent remote work flexibility.
