Data Analyst

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 

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 Analyst

Reports To: Product & Data Engineering Manager, VA  

Role Type:    Individual Contributor

        Location:     Bangalore

Role Purpose:

Design, build, and maintain the Data Analytics tools that support SKF VA data needs. By leveraging their skills in data modeling, data integration, data processing, data retrieval, data transformation and performance optimization, and data reporting, this role can help the VA data analytics team to manage and utilize their data more effectively.

Primary Responsibilities:

• Analytical Skills: Exhibit strong problem-solving abilities and attention to detail. Analyze and organize raw data and generate reports using Power BI, and Data Bricks/Azure ML Learning
• SQL Expertise: Demonstrate proficiency in SQL, including writing complex queries and optimizing SQL performance in Snowflake and dbt.
• ETL/ELT Processes: Familiarity with Snowflake’s ETL/ELT tools and techniques, as well as dbt’s transformation methods.
• Data Modeling: Possess a solid understanding of data modeling concepts and be adept with data modeling tools and techniques.
• Performance Optimization: Optimize the performance of data loading processes. This includes optimizing SQL queries, creating indexes, tuning data loading processes, and automating manual tasks.
• Security and Access Management: Manage the security and access controls of the Snowflake environment, including configuring user roles and permissions, managing encryption keys, and monitoring access logs.
• Analytics Lifecycle Maintenance: Maintain existing/new dashboards and maintain them in periodic intervals and addressing support needs, enhancements, and troubleshooting.
• Collaboration: Work closely with data scientists, analysts, and other stakeholders to understand and meet data requirements.
• Training and Support: Provide training and support to team members on the usage of Power BI and Azure data bricks tools. 

Technical Skills:

• Expertise in Azure Databricks, Azure ML Learning, and Power BI.
• Proficient in programming languages including SQL, and Python.
• Extensive knowledge in Snowflake, dbt.
• Knowledge of cloud services such as AWS and Azure.
• Knowledge in Power Automate

Candidate Profile:

• 5 - 8 Years of overall experience with minimum five years of experience as Data analyst.
• Bachelor’s degree in computer science, Information technology or a related field.