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Tier-1 brand, popular mid-level title, 3+ years range, and metro recruitment increase competition.
Core data engineering skills are transferable, though banking domain and governance add moderate bias.
Mandatory 3+ years and specific AWS, Databricks, data-modeling skills make screening strict.
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Design and deliver secure, stable, and scalable software solutions within an agile team for JPMorgan Chase's Commercial & Investment Bank.
Develop high-quality production code and maintain algorithms running synchronously with relevant systems, ensuring architectural and design constraints are met.
Analyze large, diverse data sets to identify patterns and drive improvements in software applications and system architecture, incorporating AI-assisted development tools responsibly.
At least 3 years of applied software engineering experience with formal training or certification.
Hands-on experience with AWS Services: S3, Glue, Redshift, Lambda, EMR.
Proficiency in Java, Python, and advanced SQL querying and performance tuning.
Experience in Data Modeling (Data Vault 2.0, Star, Snowflake schema), Data Quality & Governance, Databricks (Notebooks, Jobs, Delta Lake), and use of enterprise-authorized AI-assisted software development tools with ability to validate outputs.
Experienced mid-level software engineer comfortable with both backend Java/Python development and AWS cloud services focusing on data-intensive applications.
Skilled in managing data quality, governance frameworks, and advanced data modeling techniques in a complex banking technology environment.
Practitioner of responsible and secure AI tool usage in development workflows, with capability to guide peers on safe and effective integration of AI-assisted coding tools.