×
Register Here to Apply for Jobs or Post Jobs. X

Software Engineer III-Databricks

Job in Wilmington, New Castle County, Delaware, 19894, USA
Listing for: JPMorgan Chase
Full Time position
Listed on 2026-07-20
Job specializations:
  • Software Development
    DevOps, AI Engineer (Applied/Software), Cloud Engineer - Software, Machine Learning/ ML Engineer
Salary/Wage Range or Industry Benchmark: 120000 - 180000 USD Yearly USD 120000.00 180000.00 YEAR
Job Description & How to Apply Below

We have an exciting and rewarding opportunity for you to take your software engineering career to the next level.

As a Software Engineer III - Databricks at JPMorgan Chase within the Corporate Sector's Enterprise Technology team, you serve as a seasoned member of an agile team to design and deliver trusted market‑leading technology products in a secure, stable, and scalable way. You are responsible for carrying out critical technology solutions across multiple technical areas within various business functions in support of the firm's business objectives.

Job

responsibilities
  • Provides technical leadership across design, development, and troubleshooting for complex, multi-domain solutions; establish engineering standards and best practices for the team
  • Writes secure, high‑quality code in Python and/or Java; conducts reviews and mentors engineers to raise code quality and maintainability
  • Builds data pipelines using Databricks ETL
  • Builds and product ionizes cloud‑based ML pipelines; drive model deployment and operationalization in collaboration with Data Science and SRE/Platform teams
  • Owns MLOps workflows; coordinates infrastructure and production changes with SRE; ensures resiliency, observability, and security across the ML lifecycle
  • Applies SDLC tooling and automation to improve delivery velocity and reliability; champion CI/CD and cloud‑native best practices
  • Partners with Product Owners and business stakeholders to translate requirements into scalable solutions aligned to CCB Finance objectives
  • Fosters a team culture of diversity, opportunity, inclusion, and respect; model proactive learning in AI/ML and emerging technologies
  • Leverages enterprise‑authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity across complex deliverables (e.g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards; contributes learnings and reusable patterns to improve broader team effectiveness
  • Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise‑authorized AI‑assisted development and automation capabilities, to improve the value realized by automation
Required qualifications, capabilities, and skills
  • Formal training or certification on software engineering concepts and 3+ years applied experience
  • Hands‑on experience in software engineering, system design, application development, testing, and operational stability
  • Proficiency in Python; strong grounding in secure data practices
  • Hands‑on Databricks experience across Delta Lake, Unity Catalog, Workflows, Repos/notebooks, and SQL Warehouses, including cluster configuration and optimization
  • Cloud engineering experience building ML pipelines and deploying models to production with AWS services such as ECS, EMR, Lambda, EC2, Sage Maker
  • Experience with PySpark, Kafka, Terraform, and Kubernetes for data processing, streaming, IaC, and container orchestration
  • Database experience with Oracle and/or Cassandra
  • Familiarity with CI/CD, application resiliency, security best practices, Agile/Scrum methodologies, and SDLC automation tools
  • Hands‑on experience using enterprise‑authorized AI‑assisted software development tools within the work environment (e.g., for coding, test creation, troubleshooting, or documentation) with demonstrated ability to critically evaluate, validate, and refine AI-generated outputs for correctness, performance, and security
  • Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; ability to guide peers on safe and effective usage within team practices
Preferred qualifications, capabilities, and skills
  • Background with machine learning frameworks, MLOps practices, and end‑to‑end ML lifecycle management (feature pipelines, model registry, monitoring, drift detection)
  • Experience with the Python ML ecosystem (pandas, Num Py) and platforms such as Databricks for data engineering and model development at scale
  • Experience with ERWIN for…
To View & Apply for jobs on this site that accept applications from your location or country, tap the button below to make a Search.
(If this job is in fact in your jurisdiction, then you may be using a Proxy or VPN to access this site, and to progress further, you should change your connectivity to another mobile device or PC).
 
 
 
Search for further Jobs Here:
(Try combinations for better Results! Or enter less keywords for broader Results)
Location
Increase/decrease your Search Radius (miles)
0
200
Filters
Education Level
Experience Level (years)
Posted in last:
Salary