Full Stack Engineer II

Cencora•Conshohocken, PA

1d•$62,400 - $97,900•Remote

About The Position

Our team members are at the heart of everything we do. At Cencora, we are united in our responsibility to create healthier futures, and every person here is essential to us being able to deliver on that purpose. If you want to make a difference at the center of health, come join our innovative company and help us improve the lives of people and animals everywhere. Apply today! We're looking for a Full Stack Engineer II who can build and maintain applications across the stack while also working comfortably with data platforms and business intelligence tools. You'll develop features, manage CI/CD pipelines, work with large-scale data in Databricks, and translate business needs into technical and analytical solutions.

Requirements

Bachelor’s degree in computer science, software engineering, systems engineering, information technology, or a related field, or equivalent experience required.
2+ years of professional experience in full stack software development
Hands-on experience with Databricks (Spark, notebooks, Delta Lake)
Experience with Azure DevOps for CI/CD, version control, and work item tracking
Experience with Azure cloud services (Data Factory, Synapse, Functions, App Services)
Strong SQL skills and experience with relational/NoSQL databases
Frontend experience (React, Angular, or Vue) and backend experience (Node.js, Python, Java, or .NET)
Demonstrated ability to communicate with non-technical stakeholders and gather requirements
Experience with Git-based version control and Agile/Scrum workflows
Write and optimize complex SQL queries (joins, aggregations, indexing, subqueries).
Understand database schemas, normalization, and basic data modeling.
Handle data transformation logic between the database, backend APIs, and front-end states.
Experience with RESTful APIs and basic integration concepts.
Familiarity with relational databases and/or NoSQL databases.
Experience using version control systems, testing frameworks, and Agile development practices.
Understanding software development of lifecycle concepts, debugging, and quality code practices.
Strong problem-solving, communication, and teamwork skills.

Nice To Haves

Familiarity with data warehousing concepts (star schema, dimensional modeling)
Exposure to Python-based data analysis (pandas, PySpark)
Building AI/BI Dashboards/reports/traditional dashboards in Databricks/Power BI tools
Prior experience in a hybrid engineering/analytics role

Responsibilities

Design, develop, and maintain front-end and back-end components of web applications
Build and consume RESTful/GraphQL APIs integrating with internal and external data sources
Write clean, tested, maintainable code following team standards
Debug and resolve issues across the application stack
Build and optimize data pipelines and notebooks in Databricks using Python/PySpark/SQL
Support ETL/ELT processes to move and transform data across environments
Perform data analysis to support product, engineering, and business decisions — identifying trends, anomalies, and actionable insights
Independently build LLM-powered application features; apply prompt engineering, manage model behavior and token budgets, and design AI interactions that are reliable and appropriate for production use.
Integrate RAG pipelines and vector search components into application layers; work with data scientists to ensure retrieval quality meets application requirements.
Leverage AI coding assistants to accelerate development, testing, and code review tasks; validate AI-generated code critically and apply it with the same engineering discipline as hand-written code.
Analyze application telemetry, load times, bundle sizes, and query execution plans to identify bottlenecks.
Translate product KPIs or user metrics into technical tracking requirements (e.g., event logging and monitoring).
Manage CI/CD pipelines using Azure DevOps (Boards, Repos, Pipelines, Artifacts)
Participate in release management, environment configuration, and deployment automation
Monitor application and pipeline health; troubleshoot build/deployment failures
Partner directly with business stakeholders to gather requirements and clarify data/reporting needs
Translate business questions into technical specs, data models, or dashboard requirements
Present findings, dashboards, or technical updates clearly to both technical and non-technical audiences
Collaborate with product managers, designers, and other engineers in sprint planning and reviews
Participate in code reviews and uphold engineering best practices
Write and maintain technical documentation (data dictionaries, pipeline docs, runbooks)
Mentor junior engineers on specific tasks as needed