Senior Data Engineer
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Job Description
Senior Data Engineer building scalable ETL pipelines and data products for Spokeo’s people intelligence platform. Using AWS, Spark, Python, and Airflow to power large-scale public-record data systems.
Responsibilities:
- Build infrastructure and data automation pipelines to ingest, process, and load data from various sources
- Automate and integrate new components into the data pipeline
- Collaborate with stakeholders and data science teams to develop data products, including entity resolution and best selection
- Create unit and stress-test components to monitor technical performance and resolve identified issues
- Develop data analysis tools to provide data insights and capture key metrics
- Research solutions and maintain technical documentation
- Follow best practices for data governance, quality, cleansing, and other ETL-related activities
Requirements:
- 7+ years of development experience in data engineering within a production environment, excluding internships and academic settings
- Experience working with large datasets exceeding 100M+ records or multiple terabytes
- 5+ years of development experience in highly scalable, distributed systems and cluster architectures using AWS and EMR
- 5+ years of hands-on programming experience with Python
- 5+ years of professional experience in big data ecosystems
- Spark required; PySpark preferable
- 5+ years of experience with SQL, schema design, and dimensional data modeling
- 5+ years of professional experience with dataflow orchestration tools such as Airflow
- 2+ years of experience with non-relational databases such as DynamoDB or Elasticsearch
- Bachelor’s degree in Computer Science, Information Systems, Mathematics, or a related field required
Benefits:
- Bonus program
- Equity plans
- 401(k)
- Discretionary, merit-based salary increase once a year
- 100% medical, dental, and vision coverage
- Unlimited employee PTO
- Remote-first work environment
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