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Tier-1 brand, metro location, and broad technical requirements raise competition for senior data platform hires.
Technical data platform skills are transferable across industries despite financial-services preference.
Explicit 14+ years plus mandatory Databricks/Snowflake, Spark, Iceberg, IaC, and governance skills make filters stringent.
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Design, build, and operate modern data platform capabilities including lakehouse, batch and streaming pipelines, metadata/catalog, and governance layers.
Develop and optimize data pipelines using Apache Spark, Snowflake, Databricks and implement Apache Iceberg tables with performance tuning and governance.
Lead a small team to deliver scalable, reliable platform outcomes; own operational stability including incident response and root cause analysis.
14+ years software/data engineering experience.
Strong hands-on skills in Python and SQL; knowledge of Java/Scala is a plus.
Proven experience delivering data platform solutions using Databricks and/or Snowflake on cloud (AWS preferred).
Experience with Spark (batch/streaming), Apache Iceberg, CI/CD, Infrastructure as Code (Terraform/CloudFormation), and operational support responsibilities.
Experienced senior data engineer with deep expertise in large-scale data platform architecture and cloud-based distributed computing.
Able to lead small teams/pods and collaborate globally across product, analytics, ML, and business stakeholders.
Comfortable taking ownership for both delivery and operational aspects including incident management and performance optimization in a regulated, enterprise environment.