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Tier-1 brand, metro location, and broad generalist data+SRE requirements increase applicant density.
Technical data engineering and SRE skills are highly transferable across industries.
Explicit 10+ years plus mandatory data engineering, SRE, cloud, and observability skills make filters stringent.
Lead design, development, and delivery of advanced data engineering solutions with focus on reliability, scalability, and operational excellence across data platforms.
Champion and implement Site Reliability Engineering (SRE) best practices including automated monitoring, alerting, self-healing to ensure high availability and robustness.
Lead technology initiatives including root cause analysis, post-incident reviews, and vendor evaluations while fostering SRE adoption and operational improvements across teams.
10+ years of applied software engineering experience with formal training or certification.
Proficiency in Java, Python, distributed systems, cloud-native architectures, and large-scale data processing (e.g., Spark/PySpark, Databricks, Snowflake).
Demonstrated expertise applying SRE principles in complex technical environments and experience with observability tools like Dynatrace, Splunk, or Grafana.
Work Experience Required: 10+ years
Experienced leader comfortable driving multi-team adoption of AI-assisted development tools with governance and outcome measurement.
Strong background in enterprise-scale data platforms with expertise in reliability engineering, automation, and operational stability.
Skilled at collaborating across product, engineering, and operations teams to define service level objectives and improve system resiliency.