Data Engineer

Role: Senior Data Engineer

Experience:

Work Mode:

Shift Timing:

Primary Skills

• Advanced SQL Server, ETL development using SSIS, Azure Data Factory (ADF), Azure Databricks, Power BI,

  Advanced DAX (Data Analysis Expressions),

  Data Warehousing, Data Modeling, Data Quality and Validation

Job Summary

Senior Data Engineer

Key Responsibilities

• Design, develop, and maintain robust ETL workflows using

  SSIS, Azure Data Factory, and Databricks

  .
• Write complex, optimized

  SQL Server

  queries for data transformation, analysis, and reporting.
• Perform data modeling, integration, and warehousing in support of enterprise analytics initiatives.
• Support and enhance existing SSIS packages; troubleshoot and resolve issues related to older ETL pipelines.
• Develop, optimize, and publish dashboards and reports using

  Power BI

  .

• Create and maintain advanced DAX measures, calculated columns, calculated tables, KPIs, and time-intelligence calculations to support business reporting requirements.

• Design semantic models and optimize Power BI datasets for performance, scalability, and usability.

• Implement data quality checks and validation routines to ensure the accuracy and consistency of data.
• Collaborate with cross-functional teams including BI developers, analysts, and business stakeholders to translate business requirements into scalable data and reporting solutions.
• Contribute to the architecture, design, and implementation of scalable and secure data pipelines.
• Document technical designs, solutions, and processes as per organizational standards.

• Troubleshoot and optimize DAX queries, report performance, and data refresh processes within the Power BI ecosystem.

Required Skills

• 8-15 years of hands-on experience with

  Microsoft SQL Server

  and writing complex T-SQL queries.
• Strong ETL development experience using

  SSIS

  and

  Azure Data Factory

  .
• Experience with

  Azure Databricks

  for big data processing and integration.
• Willingness and capability to work with and improve legacy

  SSIS-based solutions

  .
• Strong understanding of

  Data Warehousing concepts

  , star/snowflake schema, and dimensional modeling.
• Proficiency in

  Power BI

  for data visualization, dashboard development, and reporting.

• Strong hands-on experience in writing complex DAX measures, calculated columns, calculated tables, KPIs, and time-intelligence functions.

• Experience with Power BI data modeling, semantic models, row-level security (RLS), and performance optimization.

• Strong background in

  data quality

  , cleansing, validation, and auditing.
• Experience with the

  Microsoft technology stack

  (Azure, SQL Server, SSRS, SSAS, Power BI, etc.).

• Experience working with business stakeholders to develop analytical solutions and executive dashboards using Power BI and DAX.