Job Title

Analytics Engineer

Job Description

Location: Pune, India

Experience: 2 to 4 Years

Department: Data & Analytics, Business Unit Supply

Reports To: Digital Lead/ Product Manager Analytics

Job Summary:

We are seeking a proactive and tech-savvy Analytics Engineer to join our data team. You will be responsible for building and maintaining robust data products, developing scalable data pipelines, and delivering actionable insights through advanced analytics and visualisation tools. This role requires close collaboration with internal stakeholders and to ensure data solutions are reliable, efficient, and aligned with business goals.

On a day-to-day basis, you will focus on creating and maintaining data products, data pipelines using Python, PySpark and SQL, and dashboards using tools like Qlik, or Power BI. Working in an Agile environment proactively contributes to scrum events ensuring seamless coordination with the team and swift adaptability to changing priorities. They thrive in a fast-paced, iterative development environment, where constant feedback and continuous improvement are key. 

Key Responsibilities:

• Build infrastructure to collect structured and unstructured big data.
• Design, develop, test, deploy, and maintain scalable data pipelines/ data products.
• Development of Source data products and Complex business data products.
• Integrate pipelines and reports into automated testing frameworks.
• Monitor pipeline stability and provide timely support.
• Use SQL, PySpark, or Python to retrieve, manipulate, and analyse data.
• Perform data quality assessments and derive meaningful insights.
• Create and maintain dashboards and visualisations in Tableau, Qlik, or Power BI.
• Liaise with internal stakeholders to understand data needs.
• Automate and optimise data solutions and processes.
• Manage and maintain cloud-based data platforms.
• Apply DevOps practices to manage testing and release cycles.
• Knowledge of Git or other version control tools.
• Documentation of data products and processes.
• Identify opportunities for efficiency improvements and automation.
• Share knowledge and stay updated on the latest data engineering trends.

Qualifications:

Bachelor’s, Master’s, or PhD in Computer Science, Data Science, Mathematics, Statistics, Econometrics, Operations Research, Artificial Intelligence, or a related field.

Key Competencies:

• Tech savvy and action-oriented.
• Strong collaboration and communication skills.
• Courage to take initiative and challenge the status quo.
• Demonstrates self-awareness and commitment to self-development.
• Resourceful and adaptable in dynamic environments.
• Values diversity and fosters inclusive teamwork.
• Participates actively in continuous improvement and UAT processes.
• Readiness to learn and work with Machine learning use cases.

Other Skills:

• Demonstrated interest in AI/ML use cases with willingness to learn and apply machine learning techniques to business problems.
• Excellent verbal and written communication.
• Familiarity with Agile methodologies.
• Familiarity with Supply Domain.
• Ability to initiate and discuss improvements with leadership.