Senior Data Engineer

Summary

Join People Data Labs, a fast-growing global team, and contribute to our mission of democratizing access to high-quality B2B data. As a Data Engineer, you will build and maintain infrastructure for ingesting, transforming, and loading massive datasets using technologies like Spark, SQL, AWS, and Databricks. You will develop CI/CD pipelines and build an entity resolution framework. You'll solve complex data engineering and data science problems and collaborate with stakeholders. This role requires 5-7+ years of experience in data engineering, expertise in Spark and SQL, and strong software development fundamentals. We offer competitive salaries, unlimited paid time off, comprehensive benefits, and the flexibility to work remotely.

Requirements

• 5-7+ years 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)
• Must thrive in a fast paced environment and be able to work independently
• Can work effectively remotely (able to be proactive about managing blockers, proactive on reaching out and asking questions, and participating in team activities)
• Strong written communication skills on Slack/Chat and in documents
• You are experienced in writing data design docs (pipeline design, dataflow, schema design)
• You can scope and breakdown projects, communicate and collaborate progress and blockers effectively with your manager, team, and stakeholders

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
• Devising solutions to largely-undefined data engineering and data science problems
• Work with stakeholders in Engineering and Product to assist with data-related technical issues and support their infrastructure needs

Preferred Qualifications

• 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
• Competitive Salaries
• Unlimited paid time off
• Medical, dental, & vision insurance
• Health, fitness, and office stipends
• The permanent ability to work wherever and however you want