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Sr Lead Software Engineer - Cassandra / AWS / Databricks

JPMorgan Chase
Plano, USA
Full-time
Senior · 5+ years experience
Onsite
Discovered 1 weeks ago
airflowawsaws-lambdacassandradatabricksdynatrace

Full Job Posting

Job Responsibilities

  • Design and develop innovative software solutions, applying creative problem-solving skills to address complex technical challenges.
  • Provide comprehensive production support, including batch job management, incident troubleshooting, and resolution of data delivery issues to ensure system reliability.
  • Drives adoption and governance of approved AI-assisted engineering practices across teams to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test acceleration, release readiness, incident/root-cause analysis), while establishing measurable validation standards (secure coding, peer review, automated testing) and promoting reuse of proven patterns and automation within the SDLC/TLM toolchain.
  • Applies knowledge of tools within the Software Development Life Cycle toolchain, including approved AI-assisted development and automation capabilities, to improve the value realized by automation at scale.
  • Lead automation efforts for monitoring, reporting, and operational tasks to enhance system health, efficiency, and resiliency.
  • Utilize key monitoring tools and drive process improvements to maximize system stability and performance.
  • Gather, analyze, and synthesize large, diverse data sets to develop visualizations and reporting that support continuous improvement of applications and systems.
  • Proactively identify hidden issues and patterns in data, using insights to improve coding hygiene and system architecture.
  • Collaborate with QA and Application Development teams to define and implement quality metrics for data processing, ingestion, API validation, cloud migration, and throughput testing.
  • Oversee release management and software development lifecycle activities, with hands-on experience in Jules and Jenkins pipeline deployments.

Required qualifications, capabilities, and skills

  • Formal training or certification on software engineering concepts and 5+ years applied experience
  • At least 3 years of software engineering experience with a focus on automation, monitoring, and incident management
  • Proficient in Python, Snowflake, Cassandra, Databricks, AWS, and SQL. Hands-on expertise in Python, Snowflake, Cassandra (including managing multiple clusters, diagnosis, and resiliency), and Databricks is mandatory and must be ready for full Hands-on solution building.
  • Demonstrated experience leading effective use of enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching senior engineers/leads on compliant usage patterns and controls.
  • Expert Level in Cassandra management and operational setups and linkage between Databricks Workflows/Jobs (scheduling and monitoring), Unity Catalog permissions and governance, AWS Lambda and Step Functions, and developing REST APIs using API Gateway.
  • Databricks certified and strong knowledge of Databricks and AWS Components
  • Skilled in job scheduling tools such as Autosys and Airflow
  • Experienced in performance monitoring and capacity management using Grafana, Splunk, and Dynatrace
  • Strong communication, collaboration, and problem-solving skills
  • Willing to participate in support rotations, including weekends and late shifts
  • Demonstrated experience leading effective use of enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security
  • Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching senior engineers/leads on compliant usage patterns and controls.
  • Formal training or certification on software engineering concepts and 5+ years applied

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