Project Lead - Data Engineering

• Location: Remote (India / Poland)
• Experience: 6 - 11 years
• Qualification: B.E, B.Tech, MCA, M.E, M.Tech
• Reference: RFH/07100

Tata Elxsi is among the world’s leading providers of design and technology services across industries, including automotive, broadcast, communications, healthcare, and transportation. Tata Elxsi works with leading OEMs and suppliers in the automotive and transportation industries for R&D, design, and product engineering services from architecture to launch and beyond.

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

• Strong 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