Avanade is the world’s leading Microsoft expert, helping more than 7,000 organizations modernize securely and scale AI using Microsoft technology, faster. Founded by Microsoft and Accenture, and operating as Microsoft’s Client Zero, Avanade brings deep expertise and proven delivery to simplify complexity, accelerate innovation, and deliver measurable results.
Together with Accenture, Avanade combines global scale with expertise in AI, cloud, data, cybersecurity, and ERP to design solutions that put people first. With 60,000 Microsoft professionals worldwide, 165,000 certifications, and the largest community of Microsoft MVPs, Avanade has spent more than 25 years helping organizations unlock the full potential of people and technology to create lasting impact for clients, employees, and communities.
Role Summary
Avanade India’s Data & AI practice is hiring Associate Data Engineers to work on client data platforms, reporting and AI solutions. This is an entry-level role: we look for strong fundamentals in how data moves, how it is modelled for reporting, and how AI and machine learning use it — not for a long list of tools.
You will work on a delivery team with senior engineers, building and fixing data pipelines, preparing data for reports and AI use cases, and learning our delivery and engineering practices through structured training, certification and mentoring.
Key Responsibilities
- Build and maintain simple ETL/ELT pipelines under guidance — extracting data from source systems, transforming it and loading it into the target.
- Write and tune SQL and Python code for data processing and investigate data issues through to resolution.
- Prepare and model data for reporting and build dashboards and visuals that answer a clear business question.
- Support AI and machine learning use cases — preparing and validating datasets, running exploratory analysis and helping test outcomes.
- Build proofs of concept on data, reporting and AI scenarios, and demonstrate them to client stakeholders — explaining what was built, what it shows and what it would take to make it real.
- Carry out data quality checks and reconciliation, and document the pipelines, data models and reports you work on.
- Follow team engineering practice — version control, code review, testing and deployment pipelines.
- Take part in agile ceremonies, communicate progress and blockers clearly, and complete assigned training and certifications.
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Required Skills & Experience
- 1–2 years of experience; fresh graduates are encouraged to apply.
- Bachelor’s or master’s degree in engineering, computer science or a related discipline.
- Clear understanding of ETL concepts — sources and targets, extraction, transformation, loading, incremental loads and data quality.
- Understanding of reporting and analytics fundamentals — data modelling for reporting, KPIs and metrics, and what makes a dashboard useful.
- Understanding of AI and machine learning basics — what the common model types do, how data is prepared for them, and where GenAI is and is not appropriate.
- Working knowledge of SQL and databases — tables, joins, aggregation and basic query writing.
- Programming fundamentals in Python (or a comparable language), with sound problem solving and attention to detail.
- Strong communication skills in English, written and spoken — able to explain analysis simply and present work confidently to a client audience.
- Appetite to learn quickly, and interest in building a career in enterprise data and AI.
Preferred / Good to Have
- Hands-on exposure to any ETL or data pipeline tool.
- Exposure to a BI or reporting tool.
- Exposure to a cloud platform, and any entry-level cloud or data certification.
- Familiarity with Python data libraries or distributed processing frameworks.
- Exposure to machine learning or GenAI tooling.
- Familiarity with version control and agile ways of working.
- An internship or academic project involving data, analytics or AI.
- Personal projects that show initiative and self-learning.
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