Data Engineer - People Data Labs

About Us

People Data Labs (PDL) is the provider of people and company data. We do the heavy lifting of data collection and standardization so our customers can focus on building and scaling innovative, compliant data solutions. Our sole focus is on building the best data available by integrating thousands of compliantly sourced datasets into a single, developer-friendly source of truth. Leading companies across the world use PDL’s workforce data to enrich recruiting platforms, power AI models, create custom audiences, and more.

Our Data Engineering Team is looking for individuals who can balance extreme ownership with a “one-team, one-dream” mindset. If you are looking to be part of a team discovering the next frontier of data-as-a-service (DaaS) with a high level of autonomy and opportunity for direct contributions, this might be the role for you.

What You Get to Do

• Build infrastructure for ingestion, transformation, and loading an exponentially increasing volume of data from a variety of sources using Spark, SQL, AWS, and Databricks.
• Build an organic entity resolution framework capable of correctly merging hundreds of billions of individual entities into a number of clean, consumable datasets.
• Develop CI/CD pipelines and anomaly detection systems capable of continuously improving the quality of data pushed into production.
• Dream up solutions to largely undefined data engineering and data science problems.

The Technical Chops You’ll Need

• 3-5+ years of industry experience with clear examples of strategic technical problem-solving and implementation.
• Strong software development fundamentals.
• Experience with Python.
• Expertise with Apache Spark (Java, Scala, and/or Python-based).
• Experience with SQL.
• Experience building scalable data processing systems (e.g., cleaning, transformation) from the ground up.
• Experience using developer-oriented data pipeline and workflow orchestration (e.g., Airflow preferred, dbt, Dagster, or similar).
• Knowledge of modern data design and storage patterns (e.g., incremental updating, partitioning and segmentation, rebuilds and backfills).
• Experience working in Databricks (including Delta Live Tables, data lakehouse patterns, etc.).
• Experience with cloud computing services (AWS preferred, GCP, Azure, or similar).
• Experience with data warehousing (e.g., Databricks, Snowflake, Redshift, BigQuery, or similar).
• Understanding of modern data storage formats and tools (e.g., Parquet, ORC, Avro, Delta Lake).

People Thrive Here Who Can

• Balance high ownership and autonomy with a strong ability to collaborate.
• Work effectively remotely (proactive about managing blockers, reaching out, asking questions, and participating in team activities).
• Demonstrate strong written communication skills on Slack/Chat and in documents.
• Exhibit experience writing data design docs (pipeline design, dataflow, schema design).
• Scope and break down projects, communicating progress and blockers effectively with your manager, team, and stakeholders.

Nice to Haves

• Degree in a quantitative discipline such as computer science, mathematics, statistics, or engineering.
• Experience working with entity data (entity resolution / record linkage).
• Experience working with data acquisition / data integration.
• Expertise with Python and the Python data stack (e.g., NumPy, Pandas).
• Experience with streaming platforms (e.g., Kafka).
• Experience evaluating data quality and maintaining consistently high data standards across new feature releases (e.g., consistency, accuracy, validity, completeness).

Benefits

• Stock / Equity
• Competitive salaries ($180,000 - $220,000)
• Unlimited paid time off
• Medical, dental, & vision insurance
• Health, fitness, and office stipends
• The permanent ability to work wherever and however you want