Job Details:
Role Summary
The Lead Developer, Applications is a hands‑on technical lead responsible for designing and building modern applications and data‑driven solutions that improve operational efficiency and decision‑making. This role blends application development, data engineering, and early AI/ML enablement, focusing on reducing manual processes, improving data quality, and embedding intelligence into business applications.
This position partners closely with R&D, Live Production, Planning, and Finance to deliver practical, scalable solutions—translating business needs into well‑architected applications supported by reliable data pipelines and analytics.
Key Responsibilities
Application Development & Architecture
- Lead the design, development, and enhancement of business‑critical applications, integrations, and services.
- Translate business requirements into maintainable, scalable application designs aligned with IT standards.
- Improve application usability, workflow efficiency, and error‑handling to reduce manual rework.
Data Engineering & Integration
- Design and build data pipelines and integrations between operational systems, applications, and reporting platforms.
- Implement data validation, reconciliation logic, and system controls to improve data accuracy and consistency.
- Reduce duplicate data entry by enabling system‑to‑system data flows and shared data services.
ML & AI Enablement
- Prepare and structure application data to support analytics, machine learning, and AI use cases.
- Support the development and operationalization of predictive models, anomaly detection, or optimization logic, working alongside data science or analytics partners.
- Assist in integrating ML or AI outputs into applications (e.g., recommendations, alerts, automated validations).
- Participate in early AI/ML lifecycle practices such as data preparation, model integration, deployment support, and monitoring.
Technical Leadership
- Provide hands‑on technical leadership and mentorship to application and data developers.
- Conduct design and code reviews, promoting best practices in performance, security, and maintainability.
- Partner with BI, infrastructure, and security teams to ensure solutions align with data platforms and governance standards.
Operations, Support & Continuous Improvement
- Support production applications and data integrations, including troubleshooting, root‑cause analysis, and performance tuning.
- Contribute to documentation, deployment standards, and operational runbooks.
- Identify opportunities to modernize legacy applications and introduce data‑driven automation.
Required Qualifications
- Proficiency in one or more application development languages such as C#, Java, Python, or R.
- Strong experience with SQL and relational data modeling.
- Experience building system integrations using APIs, batch jobs, or event‑based messaging.
- Solid understanding of data concepts, including data quality, transformations, and validation.
- Ability to communicate technical solutions to business and non‑technical stakeholders.
Preferred Qualifications
- Experience with data platforms or analytics tooling (Databricks, Snowflake, Synapse/Fabric, etc.).
- Exposure to machine learning workflows, including feature preparation, model scoring, or integration into applications.
- Familiarity with Python‑based data processing and ML libraries (e.g., Pandas, scikit‑learn).
- Experience with BI and visualization tools such as Power BI.
- Cloud development experience (Azure preferred).
- Experience supporting operational, manufacturing, or production systems is a plus.
Tools & Technologies (Representative)
- Languages: C#, Java, Python, SQL
- Databases: SQL Server, PostgreSQL, Oracle
- Integration: REST APIs, batch processing, messaging queues
- Data & Analytics: Azure Data Factory, Databricks, Power BI
- ML/AI Exposure: Python ML libraries, MLflow or Azure ML (supporting role)
- DevOps: Git, CI/CD pipelines, Azure DevOps or GitHub
Success Indicators (First 6–12 Months)
- Measurable reduction in manual data entry and reconciliation for key Production processes.
- Delivery of stable, data‑enabled applications that support analytics and AI use cases.
- Improved data quality and consistency across integrated systems.
- Successful integration of ML/AI insights into at least one business application.
- Positive feedback from users on application usability and data trust.
Relocation Assistance Eligible:
No
Work Shift:
1ST SHIFT (United States of America)
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