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Mid-level, common Senior Data Engineer role with broad cloud and pipeline skills in a metro market.
Requires core data engineering and cloud skills which are broadly transferable but expects enterprise-scale experience.
Explicit 5+ years plus mandatory Snowflake, cloud, Python, and data-pipeline expertise increases filter strictness.
Design, build, and maintain batch or real-time enterprise-grade data pipelines using cloud technologies such as AWS, Snowflake, Databricks.
Collaborate with data architects, product owners, data scientists, and analysts to integrate, clean, and provision data aligned with enterprise data architecture.
Lead complex data problems, provide technical thought leadership, and mentor peers on engineering best practices including CI/CD and pipeline performance monitoring.
5+ years of enterprise data engineering experience.
Proficient in Python programming and at least one of SQL, Java, R, or Spark.
Experience with cloud data platforms such as AWS, Snowflake, Databricks, Google Cloud, Glue, and Airflow.
Familiarity with data replication, integration, masking, and engineering best practices like CI/CD and testing.
Experienced in building scalable, optimized data pipelines using modern cloud databases and distributed data processing.
Able to lead technical solutions and influence engineering standards within a collaborative agile environment.
Comfortable working closely with cross-functional teams including architects, analysts, and data scientists to deliver data products at enterprise scale.