Data Engineer Lead

Job Description

Department	<Team to add>
Role	Data Engineering Lead
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Job Summary

Amara Raja Batteries is seeking an innovative and detail-oriented Data Engineering Lead to design, develop, and optimize data infrastructure across business domains. This role involves managing data pipelines, integrating multimedia data into a structured medallion data lake-house. The ideal candidate will collaborate with cross-functional teams to ensure reliable and scalable data architecture on Azure platform to support data scientists, analysts and Ai engineers.

About the Company

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Key Responsibilities

Key Accountabilities Areas

Key Activities
Data Pipeline Ownership Design, build, and maintain scalable data pipelines to integrate data from multiple systems. Enable efficient data flow for real-time monitoring and predictive analytics aligned with business objectives.
Collaboration with Data Teams Partner with data analysts and data scientists to provide clean, structured, and accessible data for advanced analytics. Collaborate to build transformation Silver pipelines and semantic Gold layer for business analytics.
IoT and Manufacturing Data Integration Integrate IoT-generated data with manufacturing systems to enable real-time insights and decision-making. Drive IT-OT convergence to enhance connectivity and visibility across digital and physical manufacturing environments.
Data Infrastructure Management Optimize data storage and processing systems to support AI and digital use cases. Develop scalable architectures to handle large volumes of high frequency transactional and slow moving enterprise data.
ETL & Workflow Automation Develop and automate ETL (Extract, Transform, Load) processes to ensure accurate and timely data integration.
Data Quality & Compliance Implement frameworks to maintain data accuracy, integrity, and security in compliance with ISO 9001 and other industry standards. Ensure adherence to data governance.

Required skills

Data Engineering Tools

Proficiency in tools like SQL, Python, or ETL frameworks for managing and processing data. Azure tools like Databricks, Azure Data Factory and Fabric.

IoT Data Integration

Understanding of IoT protocols (e.g., MQTT, OPC-UA) and ability to process IoT data for real-time insights.

Database Systems

Expertise in relational databases (MySQL, PostgreSQL) and knowledge of non-relational databases as needed.

ETL Development

Proven ability to design, automate, and optimize ETL pipelines for manufacturing data.

Cloud technologies

Broad expertise in at least one Cloud platform, preferably Azure. Working knowledge of automation and deployment tools.

Data Governance & Security

Knowledge of data governance principles and compliance with industry regulations like ISO 9001 and GDPR.

Nice to Have

Industry 4.0 Familiarity

Understanding of smart manufacturing concepts, including predictive maintenance and digital twins.

Technical Proficiency

Good understanding of DevOps, CI/CD pipelines, orchestration, and containerization tools like Docker and Kubernetes.

Qualifications

Work Experience

5-8 years of experience in data engineering, with a strong focus on Azure platform. Proven track record of integrating data from MES, ERP, CRM and manufacturing systems.

Educational Background

Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Systems, or a related field. Coursework or specialization in data architecture, analytics in Azure platform (preferred).

Preferred Industry Experience

Manufacturing, energy, or related industries with exposure to Industry 4.0.

Technical Expertise

Expertise in developing and optimizing data pipelines, ETL processes, and managing large-scale data systems in Azure (preferred). Familiarity with tools and platforms like SQL, Python, Databricks, Airflow, and IoT protocols (e.g., MQTT, OPC-UA).

Hiring Process and Next Steps

Application Process

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For queries, please reach out to:

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