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Metro location, popular Data Engineer title, and mid-level seniority increase applicant competition.
Core data engineering skills (Spark, SQL, AWS, ETL) are highly transferable across industries.
Explicit 6+ years requirement plus numerous mandatory technologies (Spark/Scala, Airflow, Hadoop, AWS, Terraform) makes filters strict.
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Build and maintain optimized, highly available data pipelines and Spark (Scala) jobs.
Contribute technically to design, deployment, and maintenance of the business data platform.
Develop metadata system for data cataloging and handle data retrieval and analysis using Spark SQL, Athena, and other tools.
Bachelor’s or master’s degree in computer science or related field.
At least 6+ years of hands-on embedded software development experience.
Proficiency with Apache Spark – Scala, Airflow, Hadoop, Impala, Sqoop, AWS services (EC2, EMR), Terraform, SQL, and Hive QL.
Experience with cloud systems (AWS/Azure), virtualization (Docker), and Agile methodologies.
Experienced in embedded software development with strong data engineering skills including Spark and AWS Cloud.
Capable of working on complex product digitalization and vehicle intelligence solutions in a central R&D environment.
Comfortable with Agile teams using tools like JIRA, Confluence, GitLab and following Lean principles.