Senior Data Engineer at Spokeo
As a Data Engineer at Spokeo, you will be responsible for developing, optimizing and maintaining the ETL data pipeline. This involves working with infrastructure built in AWS, including Spark EMR, S3, and DynamoDB. Additionally, this role will help build analytical tools, develop unit and stress tests, and create automation surrounding the scheduling of the ETL data pipeline.
- Build infrastructure and automation for the extraction, preparation, and loading of data from various sources
- Create unit and stress test components to monitor technical performance and ensure identified issues are resolved
- Build and maintain analytical tools to provide data insight and capture key metrics
- Automate and integrate new components into the data pipeline.
- Utilize best practices for data governance, data quality, data cleansing, and other ETL related activities.
- Maintain technical documentation
- 2+ years of development experience in data engineering
- 1+ years of professional experience working in big data ecosystems, such as Spark, Kafka, and Hadoop
- 1+ years of professional experience working with dataflow management and orchestration tools, such as Pentaho, Glue, Oozi, NiFi, and Airflow
- Hands-on scripting experience with Python, Scala and shell scripting
- Preference for development experience in highly-scalable, distributed systems and cluster architectures (e.g. AWS, Azure, Google Cloud, etc)
- Familiarity with complex NoSQL databases (e.g. DynamoDB, Cassandra, Elasticsearch, etc)
- Prior experience working with large data sets (>1M+ records)
- A Bachelor's degree is preferred in Computer Science, Information Systems, or related fields (foreign education equivalent accepted)
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