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Data Engineer | AI & Analytics

Job Description - Data Engineer | AI & Analytics

About Us

Acuvon Consulting is a management consulting firm with its headquarters in New Delhi, India and representative offices in Riyadh (KSA) and Dubai (UAE).

Our clients belong to a diverse set of sectors i.e. Retail, Food & Beverage, Healthcare, Fintech, Pharmaceutical, Public Sector (Government) and BFSI (including Private Equity and Family Offices).

Our mandates range from developing business strategy, growth plans and implementation roadmaps, advanced analytics and AI solutions, operational and financial restructuring, financial modelling and validation, business cycle development and process improvement, performance measurement and reporting, and commercial and financial due diligence (Buy side).

Our employees are graduates of top-tier engineering and business schools and chartered accountants and bring in a diverse set of prior experiences. We are an equal opportunity employer.

Role Summary

As a Data Engineer, you will convert business logic and AI prototypes into scalable, production-ready data pipelines, owning implementation end-to-end, from environment and connectivity setup through pipeline build, business validation, deployment and go-live support.
You will work with diverse data sources: ERP systems, databases, external sources, non-standard Excel and flat files, translating business rules into reliable, validated pipelines. You will also review the underlying SQL data models and database design, and challenge or improve them where scalability, performance or maintainability demands it.

Requirements

  • Own pipeline implementation end-to-end: environment and connectivity setup, build, validation, deployment and go-live support
  • Translate business rules and AI-generated prototypes from consulting teams into validated, production-ready pipelines
  • Integrate diverse sources: ERP systems, databases, external data, non-standard Excel and flat files
  • Define and automate tests including schema checks, row-count and value reconciliations, and failure alerts
  • Review SQL data models and database design; recommend improvements for scalability, performance and maintainability
  • Manage development and production deployments; monitor and troubleshoot pipelines in production
  • Work directly with client IT teams on connectivity, access, security and deployment requirements
Education, Experience and Skill-Set:
  • 4–7 years of relevant experience in data engineering
  • Strong hands-on experience with Azure Data Factory (ADF) (mandatory)Hands-on experience with Azure Self-Hosted Integration Runtime (SHIR) (mandatory)
  • Strong Python skills, including data validation, reconciliation and source-to-target parity matching
  • Strong grounding in SQL data modelling and database design fundamentals
  • Experience with Azure SQL and Microsoft Entra ID (preferred)
We arrange for travel to client location and also ensure comfortable accommodation at the client-site for our employees.



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