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People Data Labs

Provides B2B data solutions via APIs

Senior Software Engineer - Data Acquisition

Backend EngineeringConfirmed live in the last 24 hours
Full-timeRemote in USA

About the Job

Requirements

  • The role requires 7+ years of professional experience building or operating backend or infrastructure systems at scale.
  • The role requires solid programming experience in Python, Go, Rust, or a similar language, including experience with async/await, coroutines, or concurrency frameworks.
  • The role requires a strong grasp of software architecture and backend fundamentals, including reasoning about concurrency, scalability, and fault tolerance.
  • The role requires a solid understanding of the browser rendering pipeline and web application architecture, including authentication, cookies, and HTTP request/response.
  • The role requires familiarity with network architecture and debugging, including HTTP, DNS, proxies, packet capture, and analysis.
  • The role requires a solid understanding of distributed systems concepts, including parallelism, asynchronous programming, backpressure, and message-driven design.
  • The role requires experience designing or maintaining resilient data ingestion, API integration, or ETL systems.
  • The role requires proficiency with Linux/Unix command-line tools and system resource management.
  • The role requires familiarity with message queues, orchestration, and distributed task systems such as Kafka, SQS, or Airflow.
  • The role requires experience evaluating and monitoring data quality to ensure consistency, completeness, and reliability across releases.
  • The candidate should be able to work independently in a fast-paced, remote-first environment, proactively unblocking themselves and collaborating asynchronously.
  • The candidate should communicate clearly and thoughtfully in writing, including in Slack, documentation, and design proposals.
  • The candidate should be able to write and maintain technical design documents, including pipeline design, schema design, and data flow diagrams.
  • The candidate should be able to scope and break down complex projects into deliverable milestones and communicate progress, risks, and blockers effectively.
  • The candidate should balance pragmatism with craftsmanship, shipping reliable systems while continuously improving them.

Responsibilities

  • Contribute to the architecture and improvement of the data acquisition and processing platform, increasing reliability, throughput, and observability.
  • Use and develop web crawling technologies to capture and catalog data on the internet.
  • Build, operate, and evolve large-scale distributed systems that collect, process, and deliver data from across the web.
  • Design and develop backend services that manage distributed job orchestration, data pipelines, and large-scale asynchronous workloads.
  • Structure and model captured data, ensuring high quality and consistency across datasets.
  • Continuously improve the speed, scalability, and fault tolerance of ingestion systems.
  • Partner with data product and engineering teams to design and implement new data products powered by collected data, and enhance existing products.
  • Learn and apply domain-specific knowledge in web crawling and data acquisition, with mentorship from experienced teammates and access to existing systems.

Desired Qualifications

  • A degree in a quantitative field such as computer science, mathematics, or engineering.
  • Experience as a Red Teamer.
  • Experience working on large-scale data ingestion, crawling, or indexing systems.
  • Experience with Apache Spark, Databricks, or other distributed data platforms.
  • Experience with streaming data systems such as Kafka, Pub/Sub, or Spark Streaming.
  • Proficiency with SQL and data warehousing, such as Snowflake, Redshift, BigQuery, or similar.
  • Experience with cloud platforms; AWS is preferred, with GCP or Azure also acceptable.
  • Understanding of modern data storage and design patterns, including Parquet, Delta Lake, partitioning, and incremental updates.
  • Knowledge of modern data design and storage patterns, including incremental updating, partitioning and segmentation, rebuilds, and backfills.
  • Experience building and maintaining data pipelines on modern big-data or cloud platforms such as Databricks, Spark, or equivalent.

About the Company

People Data Labs

Provides B2B data solutions via APIs

People Data Labs provides data solutions for businesses worldwide. It collects, cleans, and enhances data to power sales and marketing, investment decisions, and data enrichment. Its products include a rich knowledge graph and APIs that let clients access person and company profiles via RESTful endpoints or SDKs; customers can run on-premise or receive bulk data deliveries for large volumes, and can query the datasets to find targeted profiles and companies. What sets PDL apart is its emphasis on a large, well-structured data catalog, strong security (SOC 2 Type 2 and ISO 27001), and trusted status with many developers and partners (SourceForge ranking). Its goal is to help customers improve decision-making and efficiency by giving them easy, secure access to accurate, up-to-date data.

Company size
51-200
Company stage
Series B
Total funding
$55.3M
Headquarters
San Francisco, CA
Founded
2015

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