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Recognized employer, popular data role, broad tech stack and metro location increase competition.
Core data engineering skills are broadly transferable across industries despite platform preferences.
Explicit 8+ years and many mandatory platform and stack requirements enforce strict filtering.
Design, implement, deploy and maintain data marts and ETL pipelines to manage data assets ensuring reliability, scalability, and performance.
Develop, maintain quality indicators with monitoring and alerting frameworks for data products.
Troubleshoot data engineering issues following company standards and continuously improve systems and processes.
8+ years of overall experience in data engineering domain with proven track record.
Proficiency in Python or Scala programming and Big Data technologies including Apache Spark, Hadoop, Hive, Kafka.
Hands-on experience with cloud platforms Azure, GCP or AWS, and data platforms such as Databricks, Snowflake, or Azure Synapse.
University degree in computer science or related field or relevant experience.
Experienced in designing and maintaining applications using Scala, PySpark, and Hadoop ecosystem components (MAPR, Kafka, Impala).
Working knowledge of data modeling, ETL process definition, and data visualization tools in agile software design environments (Scrum, Kanban, SAFe).
Familiarity with Microsoft Azure and Databricks platforms, with certifications in these areas considered beneficial.