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Mid-tier employer and metro role with popular data skills, but senior 7+ years requirement lowers applicant density.
Transferable data-engineering skills, but platform-specific tooling increases domain sensitivity.
Explicit 7+ years and multiple mandatory data-platform technologies required.
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Own building and operating real-time and batch data ingestion and transformation pipelines.
Design and enhance data platform components including storage, compute, and pipeline layers.
Develop automation tooling for monitoring, alerting, and maintaining data quality; participate in incident triage and resolution with systemic fixes.
7+ years in software or data engineering roles supporting production, high-traffic environments.
Hands-on experience building batch and real-time data pipelines with Kafka or similar streaming platforms.
Proficiency in Python and SQL; experience with Spark Structured Streaming and cloud data warehouses (Snowflake preferred).
B.S. or M.S. degree in Computer Science, Engineering, or equivalent experience.
Experienced in distributed systems with strong reliability, scalability, and fault tolerance understanding.
Demonstrates strong ownership by building and operating data infrastructure end-to-end, including on-call incident management.
Has skills leveraging AI-powered agents/tools to automate engineering and operational workflows, improving efficiency.