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