Overview

**Experience - 5+ years in Data Engineering, including hands-on cloud data platform delivery

Responsibilities

• Vserve is looking for a Senior Data Engineer to design, build, and own scalable data platforms on Microsoft Azure ecosystems. This role will lead the development of Enterprise Data Warehousing, ETL/ELT pipelines, and analytics-
• ready data models that power reporting and decision-making for our retail, wholesale, and distribution clients. The ideal candidate is equally comfortable architecting cloud-native pipelines and partnering directly with business stakeholders to translate requirements into reliable, production-grade data solutions.
• Design, build, and maintain scalable Enterprise Data Warehouse (EDW) solutions on Azure (ADF, Databricks, Azure SQL, Microsoft Fabric).
• Develop and orchestrate end-to-end ETL/ELT pipelines using Apache Airflow, Azure Data Factory, and Databricks, ensuring reliability and minimal manual intervention.
• Build and optimize PySpark transformations and Delta Lake pipelines to process large-scale datasets into curated, analytics-ready data products.
• Design dimensional data models (star/snowflake schemas), fact and dimension tables, and data marts to support sales, inventory, demand, and profitability reporting.
• Develop Power BI semantic models, datasets, and interactive dashboards enabling self-service analytics and KPI reporting for business stakeholders.
• Implement data quality and validation frameworks, including reconciliation checks, exception reporting, and automated alerting.
• Own data reconciliation between ERP/business systems (e.g., Microsoft Dynamics AX / D365 F&O, POS platforms) and the enterprise data warehouse.
• Implement complex business logic for margin calculations, cost attribution, and promotional/discount allocation to
• Build automated data ingestion frameworks using Python and REST APIs, and implement incremental loading
• Tune and optimize SQL/PL-SQL queries and data workflows for performance across high-volume, regulated, or
• Implement CI/CD for data pipelines (GitHub Actions, Git) to improve release consistency and reduce deployment
• Partner with business users, analysts, and SMEs to gather requirements and translate them into scalable, well-
• Mentor junior data engineers and contribute to data architecture and engineering best practices across the team.
• Must-Have
• 5+ years of hands-on Data Engineering experience, with demonstrated ownership of production data pipelines
• Strong experience with Microsoft Azure data services: Azure Data Factory (ADF), Databricks, Azure Data
• Hands-on expertise in Apache Spark / PySpark and Delta Lake for large-scale data processing.
• Proven experience building and orchestrating pipelines with Apache Airflow or equivalent workflow
• Advanced SQL skills and solid Python (Pandas, NumPy) programming ability.
• Strong grounding in dimensional data modeling (star/snowflake schemas, normalization, ER-diagram design).

Qualifications

• Employment Type - Full-Time
• Good-to-Have
• Exposure to Microsoft Dynamics AX / Dynamics 365 Finance & Operations (D365 F&O) or similar ERP/POS
• Familiarity with MongoDB, PostgreSQL, or DynamoDB alongside relational/warehouse platforms.
• Working knowledge of CI/CD practices (GitHub Actions, Git) and Agile delivery methodologies.
• Prior experience mentoring engineers or leading a small data engineering pod.
• Azure, ADF, Databricks, PySpark, Python, SQL, Airflow, Delta Lake, ETL/ELT, Data Warehousing, Data Modeling, Power BI, DAX, Data Quality, REST API, Git/CI-CD, D365 F&O**
• Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

Education

• Bachelor degree in Computer Science, Information Technology, or a related field is required.
• Master degree is a plus.