Data Engineer

People Data Labs provides people and company data and is hiring a Data Engineer for its data engineering team. The role builds scalable systems for data ingestion, transformation, entity resolution, and quality, and develops solutions to data engineering and data science problems.

Responsibilities:

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

Requirements:

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