Manager Data Engineering

Job Title: Lead Data Engineer (Full-Time) Department: Digital Data & Analytics (DDA) Responsibilities Techno Functional Management Manage and oversee technical and functional aspects of projects. Hands-on experience in Azure Data Factory & Data Bricks. Provide hands-on experience in Python and back-end programming languages. Utilize knowledge in data visualization tools and libraries. Knowledge in Graph-DB is a plus. People Management Lead and mentor team members, fostering a collaborative and productive work environment. Azure Data Factory & Data Bricks Design and develop data pipelines, workflows, and data transformation processes. Integrate various data sources to ensure seamless data flow between systems. Optimize data processing and storage for performance and cost-efficiency. Databases (SQL, PostgreSQL, Azure Databases) Design, implement, and maintain database systems, including PostgreSQL and Azure databases. Monitor and optimize database performance. Implement robust backup and recovery strategies. ETL/ELT Concepts Extract data from various sources. Transform data to meet business requirements. Load data into target systems efficiently. DevOps and Agile Methodologies Implement and manage continuous integration and continuous deployment (CI/CD) pipelines. Use Git for version control and collaboration. Apply Agile methodologies for project management and delivery. Cross-Team Collaboration Work closely with infrastructure teams to ensure seamless integration and deployment. Collaborate with security teams to implement and maintain security controls. Engage with business partners to understand requirements and deliver solutions in a timely and cost-effective manner. Problem-Solving and Attention to Detail Demonstrate excellent problem-solving abilities and attention to detail. Identify and resolve issues promptly within SLA guidelines, providing ongoing support to business users. Experience with data analysis, data modelling, data profiling and architecting data analytic solutions. Leadership and Team Support Lead and support the team to maintain high-quality standards in deliverables. Collaborate with cross-functional teams to support seamless project delivery. Position Responsibilities Design and develop data solutions using Azure Data Factory & Data Bricks – 40% Oversee ETL/ELT processes including managing and maintaining ETL/ELT pipelines. Extract, transform, and load data efficiently – 20% Techno Functional Management and People Management – 20% Cross-Team collaboration, DevOps & Agile methodologies – 10% Global Manufacturing Supply process understanding including production planning, quality, inventory, supply chain, MES, and SAP-ERP landscape – 10% Organizational Relationships Interacting with business stakeholders to gather integration requirements, understand business processes, and ensure that integration solutions align with organizational goals and objectives. Participate in project planning activities, risk assessment, and scheduling for DDA projects. Interacting with external vendors or partners who provide software or services that need to be integrated with DDA systems. Work with implementation partners responsible for deploying, configuring, or maintaining integrated solutions within the Zoetis IT landscape. Coordinate with developers and other members of the team to implement integration solutions, share knowledge, and address technical challenges. Education and Experience Education: Bachelor's/Master's degree in Computer Science or Applications. Experience: 8–10+ years of overall experience in Data Engineering/Science. 6+ years of hands-on experience in Data Engineering/Science. Minimum 1+ year in a lead role. Hands-on experience in Azure Data Factory and Data Bricks. Expertise in Python, database management, ETL/ELT concepts. Strong analytical skills, excellent communication abilities, and a proactive approach to problem-solving. Experience with data analysis, data modelling, data profiling, and architecting data analytic solutions. Experience with DevOps and Agile methodologies. CI/CD pipelines: Implement and manage continuous integration and deployment. Version control using Git. Technical Skills Requirements Azure Data Factory Data Bricks ETL/ELT Database Management (SQL, PostgreSQL, Azure Databases) Python Data Visualization Tools CI/CD Pipelines Git Graph-DB (Preferred) Physical & Work Schedule Requirements Regular working hours: 11:00 AM to 8:00 PM IST Occasional EST overlap required during production go-lives