Job Purpose

Responsible for supporting the development and maintenance of data pipelines, semantic models, and business intelligence solutions to deliver reliable and accessible data for reporting and decision-making. Assists with data transformation, quality validation, reporting development, and stakeholder support while building foundational expertise in data engineering and analytics.

Key Result Responsibilities

- Assist in building and maintaining ELT/ETL pipelines that source, clean, and transform data for analytics consumption
- Write well-structured, documented SQL and dbt models to support data transformation and semantic layer development
- Support the development and maintenance of Power BI reports and dashboards under the guidance of senior engineers
- Help maintain and document data models in Snowflake or Azure Synapse, including basic schema design and table structures
- Perform data validation and quality checks to ensure accuracy and consistency of reporting outputs

Key Result Responsibilities-Continued
- Monitor scheduled pipeline runs and report data quality or performance issues with sufficient context for resolution
- Maintain documentation for pipelines, data flows, semantic model definitions, and report logic




- Participate in code reviews and team discussions to build awareness of engineering and analytics standards
- Collaborate with analysts and business stakeholders to understand reporting requirements and translate them into data tasks

Qualifications (Academic, Training, Languages)

- Bachelor's degree in Computer Science, Information Technology, Business Analytics, Statistics, or a related field.
- Fluent in English langage.
- Proficiency in SQL; exposure to Python is an advantage
- Basic familiarity with Power BI — creating reports, straightforward DAX measures, and working with data models
- Understanding of core data concepts: joins, aggregations, data types, and basic normalization
- Awareness of ELT/ETL processes and how data flows from source systems to reporting layers
- Basic familiarity with data warehousing concepts (facts, dimensions, star schema)
- Understanding of version control using Git
- Exposure to cloud data platforms such as Azure, AWS, or GCP

Work Experience
- With 1–2 years of experience in data engineering, analytics, BI development, or a related technical role (including internships or academic projects).
- ITIL Certification is an advantage but not mandatory

📌 Associate Data Analytics Engineer (Pune)
🏢 ISA
📍 Pune