About SKF

SKF started its operations in India in 1923. Today, SKF provides industry leading automotive and industrial engineered solutions through its five technology-centric platforms: bearings and units, seals, mechatronics, lubrication solutions and services. Over the years the company has evolved from being a pioneer ball bearing manufacturing company to a knowledge-driven engineering company helping customers achieve sustainable and competitive business excellence.

SKF's solutions provide sustainable ways for companies across the automotive and industrial sectors to achieve breakthroughs in friction reduction, energy efficiency, and equipment longevity and reliability. With a strong commitment to research-based innovation, SKF India offers customized value-added solutions that integrate all its five technology platforms.

To know more, please visit: www.skf.com/in

SKF India has been recognized as a "Top Employer 2024" by the Top Employers Institute, acknowledging excellence in People Practices.

To know more, Please visit: https://www.skf.com/in/news-and-events/news/2024/2024-01-18-skf-india- recognized-as-top-employer-2024-by-top-employers-institute

About Automotive

SKF is a leading global supplier in the automotive industry, providing solutions for various applications such as wheel end, powertrain, driveline, and suspension. SKF's automotive business is focused on delivering innovative solutions to OEMs and the aftermarket. The company has a strong presence in the automotive market, with a range of products and services designed to improve performance, reduce friction, and increase efficiency. SKF's automotive business is constantly evolving to meet the changing needs of the industry, with a focus on sustainability, electrification, and digitalization.

SKF Purpose Statement

Together, we re-imagine rotation for a better tomorrow.

By creating intelligent and clean solutions for people and the planet

JOB DESCRIPTION

Job Title : Data Engineer

Reports To : Product & Data Engineering Manager, Vehicle Aftermarket

Role Type : Individual Contribution

Location : Bangalore

Role Purpose :

Design, build, and maintain the data infrastructure and systems that support SKF VA data needs. By leveraging their skills in data modeling, data integration, data processing, data storage, data retrieval, and performance optimization, this role can help VA manage and utilize their data more effectively.

Key Responsibilities

• Build a VA data warehouse which is scalable, secured, and compliant using Azure technologies. This includes designing and developing data models within Azure Synapse Analytics.
• Work with Central data warehouses like SDW, MDW, OIDW to extract data and enrich with VA-specific customer grouping, program details, etc.
• Data integration: Integrate data from ERP’s, BPC and other systems into Snowflake, SKF standard DW’s ensuring that data is accurate, complete, and consistent.

• Performance optimization: Optimize the performance of Snowflake queries and data loading processes. Involves optimizing SQL queries, creating indexes, and tuning data loading processes.
• Security and access management: Manage the security and access controls of the Azure environment. This includes configuring user roles and permissions, managing encryption keys, and monitoring access logs.
• Maintain existing databases and warehouse solutions, addressing support needs, enhancements, and troubleshooting.
• Leverage Azure services such as Azure Data Factory (ADF), Azure Storage Account, and Azure Synapse Analytics to enhance data storage, processing, and analytics capabilities.
• Implement and manage data pipelines using DataBricks and PySpark for efficient data processing.
• Integrate AI/ML models for advanced data analytics and insights.
• Utilize Python programming for data manipulation, transformation, and automation tasks.
• Manage data workflows using Azure Data Factory (ADF), Azure DevOps, and Power Automate.
• Ensure efficient data storage and retrieval using Azure SQL Database and Azure Storage Account.
• Apply knowledge of Azure Functions and Batch Services for scalable data processing.
• Fair knowledge of Hadoop for handling large data sets.

Metrics:

• Technical Metrics: Data quality for the whole of VA BU, data processing time, data storage capacity, and systems availability.

• Business Metrics: Data-driven decision-making, data security and compliance, cross-functional collaboration.
  

Competencies:

• Good understanding of data modeling concepts and familiarity with Azure Synapse Analytics data modeling tools and techniques.
• Expertise in SQL, with the ability to write complex SQL queries and optimize SQL performance in Azure SQL Database.
• Familiarity with Azure Data Factory (ADF) and other Azure ETL/ELT tools and techniques.
• Strong understanding of cloud computing concepts with a focus on Azure infrastructure and services.
• Good understanding of data warehousing concepts and familiarity with Azure Synapse Analytics.
• Familiarity with data governance and security concepts.
• Ability to identify and troubleshoot issues with Azure data infrastructure.
• Experience with Agile solution development.
• Strong experience with Azure, including Azure ADF, DataBricks, Azure DevOps, Azure SQL Database, Azure Storage Account, and Synapse Analytics.
• Proficiency in Python programming for data-related tasks.
• Experience integrating AI/ML models for data analytics.
• Knowledge of Azure Functions and Batch Services.
• Familiarity with Power Automate for workflow automation.
• Fair knowledge of Hadoop for handling large-scale data processing.
• Proficiency in PySpark for big data processing.
• Experience with the deployment of data applications in Azure.
• Experience in developing and maintaining dashboards in Azure.
• Good to have – knowledge of SKF ERP systems (XA, SAP, PIM, etc.), data-related sales, supply chain data, and manufacturing.

Candidate Profile :

• Bachelor’s Degree in computer science, Information technology or a related field
• 5-8 Years of relevant functional work experience;
• Strong experience with Azure is essential.