Data Analyst - Aftersales Analytics

Join our Data Analytics team and be a key player in developing innovative, data-driven solutions for Aftersales.

We are looking for team-oriented, responsible, and passionate professionals who thrive on innovation and want to help shape our Aftersales data strategy. Your focus will be on applying intelligent data analysis to generate valuable business insights, directly impacting strategic decisions and operational efficiency.

If youre excited about data engineering, decentralized architectures, and building high-impact data products, wed love to hear from you!

JD of the position

• Roles & Responsibilities

  • Design & Build Scalable Data Solutions
  • Improve data processing efficiency, ensuring scalability, speed, and reliability.
  • Work closely with data scientists, analysts, and business teams, product owners to understand data needs and deliver reliable, well-structured products.
  • Mentor junior engineers, conduct code reviews, and promote best practices in data engineering.
  • To maintain existing dashboards and identify/derive new KPI / metrics that help data driven decision making
  • Perform complex joins / aggregation in powerbi using DAX to derive the required data models / metrics / KPI etc.

• Mandatory:

  • 4+ years experience in Data Engineering.
  • Deep hands-on expertise in Databricks, Python, SQL queries.
  • Working knowledge in PowerBI, report server, data models etc.

• Must be experienced in

  • Working as a Big Data Engineer: query tuning, performance tuning.
  • Data architecture patterns (Data lakehouse, delta lake, streaming, Lambda/Kappa architecture).
  • A full range of data engineering approaches, covering theoretical best practices and the technical applications of these methods.
  • Building and deploying a range of data engineering pipelines into production, including using automation best practices for CI/CD.
  • Troubleshooting, and debugging Spark and other big data solutions.
  • Writing SQL queries.
  • Databases and analytics technologies Data Warehousing/ETL/ELT, Relational Databases, or MPP
  • Experience using code management tools such as Github Actions, Jenkins or Azure DevOps and cloud computing platforms such as Azure, AWS
  • Good experience with Azure Databricks / delta tables / Hive / Parquet files, and other components in Azure tech stack

• Must be familiar with

  • Azure cloud and creating Azure ADF pipelines.
  • Data analytics and complex event processing.
  • Strong understanding of Agile methodologies and experience working in Scrum teams, contributing to sprints, backlog refinement, and iterative development.
  • Excellent communication (written and verbal).
  • Experience working automotive sales and marketing data preferrable.