Key Responsibilities

Technical Leadership

- Lead the design, development, and implementation of scalable data engineering solutions for enterprise-wide data and analytics initiatives.
- Drive technical decisions and ensure adherence to architecture standards, data governance, security, and best practices.
- Design and optimize ELT/ETL pipelines using technologies such as Snowflake, Apache Airflow, DBT, Matillion, and cloud-native services.
- Ensure high availability, performance, scalability, and cost optimization of data platforms.

Project Delivery & Stakeholder Management

- Manage multiple data engineering projects, ensuring timely delivery, quality outcomes, and alignment with business objectives.
- Collaborate with data architects, analysts, data scientists, ML engineers, and business stakeholders to translate requirements into technical solutions.
- Track project milestones, risks, dependencies, and resource utilization.
- Provide status updates and technical recommendations to leadership and stakeholders.

Team Leadership

- Lead and mentor a team of data engineers, promoting engineering excellence and continuous improvement.
- Conduct technical reviews, guide solution design discussions, and support team development.
- Establish coding standards, automation practices, and reusable frameworks to improve productivity.

Platform & Process Improvement

- Drive proof-of-concepts (POCs), innovation initiatives, and technology evaluations.
- Enhance platform reliability, monitoring, observability, and operational efficiency.
- Support DevOps and DataOps practices through automation and CI/CD implementation.

Required Skills & Qualifications

Experience

- 6-8 years of experience in Data Engineering, Data Platform Development,



or related roles.
- Proven experience leading technical projects and coordinating cross-functional teams.

Technical Skills

- Strong expertise in Snowflake or equivalent cloud data warehouse technologies.
- Hands-on experience with Apache Airflow, DBT, and Matillion or similar data integration tools.
- Strong SQL skills and experience in data modeling, schema design, and query optimization.
- Experience building cloud-native data solutions on Azure (preferred) and/or AWS.
- Strong knowledge of ETL/ELT architectures, data pipelines, and workflow orchestration.
- Experience with Python or similar programming languages for data engineering and automation.

Leadership & Soft Skills

- Robust project planning, stakeholder management, and communication skills.
- Ability to drive technical discussions and influence architectural decisions.
- Excellent analytical and problem-solving capabilities.
- Experience mentoring and guiding junior engineers.

Preferred Qualifications

- Experience with Power BI or other visualization and reporting platforms.
- Knowledge of AI/ML concepts and supporting machine learning workflows.
- Experience with Docker, Kubernetes, Azure Container Services, AWS Fargate, or similar containerization technologies.
- Exposure to CI/CD pipelines and infrastructure-as-code practices.
- Experience working in Agile/Scrum environments.

Educational Qualification

- Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or a related field.

Key Competencies

- Technical Leadership
- Project Management
- Stakeholder Collaboration
- Cloud Data Engineering
- Data Architecture & Modeling
- Team Mentoring
- Problem Solving
- Continuous Improvement & Innovation

📌 Project Lead - Data Engineering (India)
🏢 Tata Elxsi
📍 India