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People Data Labs

Provides B2B data solutions via APIs

Data Engineer

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

About the Job

Requirements

  • Three to five or more years of industry experience with examples of strategic technical problem-solving and implementation.
  • Strong software development fundamentals.
  • Experience with Python.
  • Expertise with Apache Spark using Java, Scala, and/or Python.
  • Experience with SQL.
  • Experience building scalable data processing systems, such as cleaning and transformation systems, from the ground up.
  • Experience using developer-oriented data pipeline and workflow orchestration tools, such as Airflow, dbt, or Dagster.
  • Knowledge of modern data design and storage patterns, including incremental updating, partitioning and segmentation, rebuilds, and backfills.
  • Experience working in Databricks, including Delta Live Tables and data lakehouse patterns.
  • Experience with cloud computing services such as AWS, GCP, or Azure.
  • Experience with data warehousing tools such as Databricks, Snowflake, Redshift, or BigQuery.
  • Understanding of modern data storage formats and tools such as Parquet, ORC, Avro, and Delta Lake.
  • Ability to balance high ownership and autonomy with collaboration.
  • Ability to work effectively remotely, proactively managing blockers, asking questions, and participating in team activities.
  • Strong written communication skills using Slack/chat and documents.
  • Experience writing data design documents covering pipeline design, dataflow, and schema design.
  • Ability to scope and break down projects and communicate progress and blockers with the manager, team, and stakeholders.

Responsibilities

  • Build infrastructure for ingesting, transforming, and loading increasing volumes of data from varied sources using Spark, SQL, AWS, and Databricks.
  • Build an organic entity resolution framework that correctly merges hundreds of billions of individual entities into clean, consumable datasets.
  • Develop CI/CD pipelines and anomaly detection systems that continuously improve the quality of data released to production.
  • Develop solutions to undefined data engineering and data science problems.

Desired Qualifications

  • A degree in a quantitative discipline such as computer science, mathematics, statistics, or engineering.
  • Experience working with entity data, including entity resolution or record linkage.
  • Experience working with data acquisition or data integration.
  • Expertise with Python and the Python data stack, such as NumPy and pandas.
  • Experience with streaming platforms such as Kafka.
  • Experience evaluating data quality and maintaining high data standards across feature releases, including consistency, accuracy, validity, and completeness.
  • Experience with Airflow.
  • Experience with AWS.

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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