Overview

Location: India (Offshore)

Responsibilities

• Design, develop, and maintain end to end data pipelines using Azure Data Factory, Azure Databricks, and SQL
• Implement and support Bronze, Silver, and Gold transformations using lakehouse and medallion architecture patterns
• Ingest, transform, and integrate data from ERP, CRM, and operational systems
• Optimize data pipelines for performance, reliability, and cost
• Monitor, troubleshoot, and support production data workflows
• Design and implement analytical data models (fact/dimension, star schema) with clearly defined grain, keys, and relationships
• Create curated datasets and semantic-ready data domains that standardize KPI logic and business rules
• Ensure consistent metric definitions and data logic across sources to support enterprise reporting and analytics
• Partner with stakeholders to validate requirements, definitions, and acceptance criteria for analytics deliverables
• Develop and support Power BI semantic models, datasets, and reports aligned to enterprise data standards
• Troubleshoot and optimize refresh reliability, model performance, and data-related reporting issues
• Provide end-user and stakeholder support, including issue triage, root-cause analysis, and clear documentation
• Enable AI-assisted analytics and agent-driven use cases by delivering well-modeled, well-documented datasets and clear schemas
• Use LLM-powered tools to accelerate code scaffolding, documentation, and pattern development; ensure all outputs are reviewed, tested, and production-ready
• Support lightweight automation/agent workflows for well-defined tasks within approved guardrails and controls
• Implement data quality rules, validation checks, and reconciliation tests to ensure dataset accuracy and completeness
• Apply logging, monitoring, and basic observability so pipelines and automated workflows are reliable and auditable
• Follow Azure security and access-control practices, including role-based access control (RBAC)
• Document pipelines, transformations, models, and KPI logic for traceability, lineage, and support
• Participate in CI/CD and release processes using Azure DevOps
• Work with a variety of teams, including data, system, and business teams, to understand requirements and deliver reliable data solutions
• Collaborate with onshore and offshore teammates, following established standards and designs, and communicate clearly to ensure solutions are understandable, repeatable, and maintainable

Qualifications

• Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or related field
• 3+ years of experience in data engineering, analytics engineering, or BI engineering
• Strong SQL skills (complex joins, transformations, performance tuning)
• Hands-on experience with:
• Azure Databricks
• Azure Data Factory or similar orchestration tools
• Lakehouse/medallion architecture patterns
• Familiarity with CI/CD, version control, and production support practices
• Strong problem-solving, communication, and documentation skills
• Knowledge of Delta Lake, data validation, or data observability concepts
• Exposure to AI assisted analytics, conversational BI, or agent based workflows
• ERP or CRM data experience (e.g., JD Edwards, Salesforce)
• Azure or Databricks certifications (e.g., DP 203 or equivalent)
• Production data pipelines are reliable, monitored, and well documented
• Analytics data models and semantic domains consistently support enterprise KPIs and reporting
• Power BI datasets and reports refresh reliably and perform well for end users
• Data quality and validation reduce defects and improve trust in reporting
• Stakeholders receive timely support, clear communication, and actionable documentation
• Data products are ready to support AI-assisted analytics and controlled agent-enabled workflows

Nice to have

• Working knowledge of Python for data engineering, automation, or notebook based workflows