Senior Data Engineer

We are seeking a highly skilled Senior Data Engineer to build and maintain scalable, highperformance data solutions that unify information from multiple systems into a single, trusted source of truth. This role spans the full data engineering lifecycle, including ingestion, transformation, integration, modeling, and performance optimization.

The ideal candidate will have strong handson expertise in dimensional modeling, ETL development (ADF, SSIS, Python), advanced SQL, and data quality management, while also supporting analytics and reporting teams. The position requires close collaboration with business stakeholders and adherence to engineering best practices to deliver accurate, consistent, and analyticsready data across the organization.

Data Engineering: Design, develop, and maintain enterprise-grade data warehouse solutions supporting reporting, analytics, and operational workloads.

Single Source of Truth: Integrate and standardize data from multiple systems to establish a unified, trusted data foundation.

Scalable Data Solutions: Translate business requirements into scalable data models and robust engineering solutions.

Dimensional Modeling: Convert business entities into wellstructured facts and dimensions using dimensional modeling best practices.

Data Modeling: Design and maintain relational schemas, ER models, and optimized normalization/denormalization strategies.

ETL Development: Develop, enhance, and maintain ETL pipelines using ADF, Microsoft SSIS, Python, or similar tools.

Data Quality Assurance: Ensure data accuracy, consistency, and reliability throughout ingestion and transformation processes.

Data Integration: Integrate data from Oracle NetSuite, Salesforce, Ragic, SQL Server, MySQL, Excel, and other internal/external systems.

SQL Development: Write and maintain complex SQL queries, stored procedures, functions, triggers, and views.

Performance Optimization: Implement indexing strategies, tune queries, and optimize database performance for efficiency and speed.

Issue Resolution: Troubleshoot and resolve data, performance, and availability issues in production environments.

Reporting & Analytics Enablement: Support reporting and analytics initiatives using Power BI, SSRS, or similar tools.

Collaboration: Work closely with developers, analysts, and business stakeholders to gather requirements and deliver endtoend solutions.

Documentation: Maintain comprehensive documentation for data models, ETL pipelines, database objects, and workflows.

Governance & Change Management: Follow best practices for version control, deployment, and change management using Git and JIRA.

Must have

oBachelors or Masters degree in Computer Science, Information Technology, or a related field.

o7+ years of experience with Azure SQL, Microsoft SQL Server and Data Engineering solutions.

oStrong expertise in SQL Serverbased data warehousing

oHands-on experience Dimensional Modeling using Facts and Dimensions.

oExpertise in ADF, SSIS and Python for ETL development.

oAdvanced SQL skills (complex queries, stored procedures, performance tuning).

oStrong experience in Power BI & SSRS for reporting and data visualization.

oStrong understanding of relational database design, indexing, and performance tuning.

oAbility to write complex SQL scripts, stored procedures and views.

oFamiliarity with Git, JIRA, and collaborative development workflows.

oProblem-solving mindset and analytical skills.

oExcellent communication and documentation abilities.

Nice to Have

oExperience with cloud data platforms such as Azure Fabric, or similar.

oExposure to cloud-based ETL and data processing tools (Databricks).

oKnowledge of CI/CD pipelines for database and data platform deployments.

oExperience with MySQL/Oracle or other relational databases.

oExperience with automation and scripting (PowerShell).

oRelevant certifications (e.g., Microsoft Azure Database, AWS Database Specialty)