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Metro location, popular data-platform role, and broad tech stack increase candidate competition.
Role requires regulated-finance exposure and deep data-platform expertise, making cross-industry fit somewhat limited.
Explicit 15+ and 10+ year requirements plus many mandatory platform technologies drive high screening strictness.
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Design, build, and maintain scalable, secure cloud-native data platforms on AWS or Azure optimized for performance, cost, and reliability.
Develop, optimize, and automate data pipelines for structured and unstructured data supporting analytics, AI/ML workloads, and enterprise use cases.
Manage operational health, implement governance/compliance standards including data quality, security controls, and disaster recovery strategies.
Bachelor’s degree in Computer Science, Data Engineering, or related field; Master’s preferred.
15+ years total work experience; 10+ years in data engineering, cloud engineering, or platform engineering.
Hands-on experience with major cloud providers (AWS or Azure) and big data processing frameworks (e.g., Spark, Databricks).
Experience with cloud data platforms (e.g., Snowflake, Databricks), data pipeline tools (e.g., Apache Airflow, dbt, Kafka), and exposure to regulated environments (financial services or healthcare).
Senior-level technologist with strong design judgment and ability to influence cross-functional teams without direct authority.
Experienced in building secure, compliant data platforms in regulated industries with deep cloud-native data services knowledge.
Able to mentor and uplift engineering teams while driving innovation and adoption of emerging cloud data technologies.