Data Warehousing Specialist
$183,851–$202,236 year
HybridLos Angeles, California, United States
Job Summary
Design and develop robust, scalable data engineering solutions using Python, PySpark, and Snowflake to build distributed, low-latency pipelines for Big Data and streaming workloads. Implement real-time data ingestion, orchestration with Apache Airflow, and automated validations to ensure high availability and data quality. Create technical design documentation, troubleshoot data issues, and collaborate with Agile, analytics, and business teams to optimize data models for decision-making. Manage end-to-end automation, security controls, and encryption while staying current with emerging technologies to educate the team.
Required Qualifications
- Bachelor's degree in Computer Science, Computer Engineering, Data Science, Mathematics, Statistics, Engineering or related field
- Five (5) years of progressive, post-baccalaureate data engineering experience
- Experience in architecting, designing and building data engineering solutions and data platforms
- Experience building data engineering pipelines using Python and PySpark
- Experience building Lakehouse or batch/streaming data pipelines in Databricks
- Experience in Data warehousing on Snowflake
- Experience in Data acquisition and transformation tools such as Fivetran and dbt
- Experience in Real-time data stream processing using Apache Kafka, Kinesis, or Spark structured streaming
- Experience in Distributed data processing frameworks such as Apache Hadoop, Apache Spark, or Flink
- Experience in Automated workflow scheduling and orchestration tools such as Astronomer or Apache Airflow
- Experience in Various AWS services including S3, EC2, EMR, Lambda, RDS, Redshift, and Glue Catalog
- Telecommuting up to 25%/week within normal commuting distance of Fox office in Los Angeles, CA
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