Application Developer III

We Are Teva
We’re Teva, a leading innovative biopharmaceutical company, enabled by a world-class generics business. Whether it’s innovating in the fields of neuroscience and immunology or delivering high-quality medicine worldwide, we’re dedicated to addressing patients’ needs now and in the future. Here, you will be part of a high-performing, inclusive culture that values fresh thinking and collaboration. You'll have the room to grow, the flexibility to balance life with work, and the opportunity to better health worldwide, together.
Our Team, Your Impact
The Application Developer III, Commercial Data Platforms is a hands-on technical role responsible for designing, developing, enhancing, and supporting Teva's Commercial Data Platforms ecosystem. This position partners closely with business stakeholders, product owners, architects, data engineers, and analytics teams to deliver scalable, secure, and high-performing data and analytics solutions that support critical commercial functions including Sales, Marketing, Commercial Analytics, Field Operations, Incentive Compensation, Forecasting, Market Access, and Data Governance.
The candidate will play a key role in building next-generation data platforms, developing cloud-native data solutions, and driving the adoption of modern engineering practices. The role requires deep expertise in Databricks, cloud data engineering, SQL, Python, data integration, and analytics technologies to enable enterprise reporting, advanced analytics, AI-driven insights, and business intelligence capabilities.
The successful candidate will contribute to Teva's cloud transformation strategy by modernizing legacy platforms, optimizing data pipelines, improving operational efficiency through automation, and delivering innovative solutions that accelerate business value and decision-making.
How You’ll Spend Your Day
Data Engineering & Solution Development
Design, develop, test, and deploy scalable data pipelines, data products, and analytics solutions supporting commercial business processes.
Develop and maintain enterprise-grade ETL/ELT solutions for ingesting, transforming, and curating data from multiple internal and external sources.
Build and optimize data workflows using Databricks, PySpark, Spark SQL, Delta Lake, and cloud-native technologies.
Develop reusable frameworks and components that improve development productivity and platform consistency.
Collaborate with business analysts and product owners to translate business requirements into scalable technical solutions.
Design and implement robust data models to support reporting, analytics, and operational use cases.
Ensure high levels of performance, reliability, data quality, and scalability across data platforms.
Develop APIs and integration solutions to support downstream applications and data consumers.
Databricks Platform Engineering
Lead development activities on the Databricks Lakehouse Platform.
Design and optimize Delta Lake architectures supporting enterprise-scale analytical workloads.
Develop and manage Databricks Workflows, Jobs, Notebooks, Asset Bundles, and deployment pipelines.
Implement Unity Catalog standards and governance controls to enable secure and compliant data access.
Optimize Spark workloads and cluster utilization for performance, scalability, and cost efficiency.
Support migration of legacy ETL and warehouse workloads to Databricks Lakehouse architecture.
Implement monitoring, observability, and operational controls for Databricks environments.
Establish and promote Databricks development standards and best practices.
Commercial Data Platform Delivery
Develop solutions supporting Sales Analytics, Customer Analytics, Incentive Compensation, Forecasting, Field Force Effectiveness, Market Access, and Commercial Reporting.
Build and maintain reporting and dashboarding solutions that support commercial decision-making.
Support data onboarding and integration of pharmaceutical commercial data assets.
Participate in product launch initiatives by enabling launch analytics, performance tracking, and business intelligence capabilities.
Ensure accurate and timely delivery of commercial data across enterprise platforms.
Partner with Data Governance and Business Analytics teams to improve data quality and business adoption.
Contribute to enterprise cloud transformation initiatives and platform modernization programs.
Develop cloud-native solutions leveraging AWS, Azure, Databricks, and modern data architecture patterns.
Implement CI/CD pipelines, automated testing, build automation, and deployment frameworks.
Identify opportunities to automate operational processes and reduce manual interventions.
Support Infrastructure as Code and DevOps practices across the data platform ecosystem.
Drive continuous improvement initiatives focused on reliability, operational excellence, and developer productivity
Required Skills
Operational Excellence & Support
Monitor platform performance and proactively identify optimization opportunities.
Troubleshoot complex production issues and perform root cause analysis.
Support incident management, problem management, and service improvement initiatives.
Participate in application releases, deployments, upgrades, and platform maintenance activities.
Ensure compliance with enterprise security, governance, validation, and change management processes.
Develop and maintain technical documentation, architecture diagrams, support runbooks, and operational procedures.
Support SLA adherence and platform availability objectives.
Collaboration & Technical Leadership
Collaborate with architects, engineers, analytics teams, business stakeholders, and external vendors.
Participate in solution design reviews, code reviews, and architecture discussions.
Mentor junior developers and provide technical guidance on engineering best practices.
Promote reusable design patterns, coding standards, and development methodologies.
Stay current on emerging technologies, modern data architectures, AI capabilities, and cloud innovations.
Contribute to innovation initiatives and proof-of-concept development efforts
Your Qualification And Experience
Bachelor's degree in Computer Science, Information Systems, Software Engineering, Data Engineering, Data Analytics, or a related technical discipline required.
Master's degree preferred.
3-5+ years of experience in Data Engineering, Data Warehousing, Analytics Platforms, or Software Development roles.
3+ years of hands-on Databricks development experience in enterprise environments.
Strong experience designing and developing large-scale data pipelines and analytics solutions.
Advanced SQL development and query optimization skills.
Strong Python and PySpark programming expertise.
Experience developing ETL/ELT frameworks and data integration solutions.
Strong understanding of Data Warehouse, Data Lake, and Lakehouse architectures.
Experience working with cloud platforms such as AWS and/or Azure.
Experience implementing CI/CD and DevOps practices.
Strong analytical, troubleshooting, and problem-solving capabilities.
Experience working in Agile delivery environments.
Excellent communication, collaboration, and stakeholder management skills.
Ability to work independently while contributing effectively to cross-functional teams.
Technical Competencies
Databricks & Lakehouse Platform
Databricks Lakehouse Platform
Delta Lake
Unity Catalog
Databricks SQL
Databricks Workflows
Databricks Asset Bundles
Workspace Administration
Cluster Management and Optimization
Performance Tuning
Lakehouse Architecture
Medallion Architecture
Streaming and Batch Processing
Data Engineering & Analytics
Enterprise Data Warehousing
Data Lakes and Lakehouse Platforms
Data Modeling (Dimensional, Star Schema, Data Vault)
Master Data Management (MDM)
ETL/ELT Development
Data Integration
Data Quality Frameworks
Metadata Management
Data Lineage and Governance
Business Intelligence and Reporting
Advanced Analytics Enablement
Cloud Technologies
AWS
S3
Glue
Lambda
Redshift
IAM
CloudWatch
Azure
Azure Data Lake Storage (ADLS)
Azure Data Factory
Azure SQL
Synapse Analytics
Azure DevOps
Programming & Development
SQL
Python
PySpark
Spark SQL
REST APIs
JSON/XML Processing
Git/GitHub
Object-Oriented Programming
Test-Driven Development
Code Review Practices
DevOps & Engineering Excellence
CI/CD Pipelines
Azure DevOps
GitHub Actions
Release Automation
Infrastructure as Code Concepts
Agile and Scrum Methodologies
Monitoring and Observability
Production Support
Service Reliability Engineering
Reporting & Visualization
Tableau
Power BI
Data Visualization Tools

Skills
Python, REST API, Git, AWS, Azure, CI/CD, SQL

Experience
3+ yrs

Work arrangement
No