ETL Developer

Experience Range : 6 to 9 years

Minimum Qualifications :

6+ years of

SQL Server development

experience ( SQL Server 2012

and later)

6+ years working with

ETL / ELT tools such as SSIS, Informatica

6+ years optimizing SQL queries and SSIS packages for performance

6+ years working with data warehousing concepts and dimensional modeling (e.g., Star Schema)

6+ years in data modeling and database design

3+ years developing SSAS Tabular and / or Multidimensional models, with MDX

3+ years experience building dashboards using

Power BI and DAX

(or equivalent)

4+ years working with XML, JSON, PowerShell, and REST APIs

4+ years of Azure data platform implementation experience

Strong T-SQL skills for data manipulation and stored procedure development

Experience with both on-premises and cloud BI environments (e.g., Azure SQL DB, Azure Data Factory, Power BI Service)

Good understanding of data quality, validation techniques, and governance practices

3+ years using Agile tools like Jira, Bitbucket, Confluence

3+ years working with ticketing tools like ServiceNow, JIRA, or Quality Center

Experience with SharePoint for document collaboration

High proficiency with Microsoft Office tools

Strong communication skills across technical and business teams

Ability to work independently and collaboratively in distributed teams

Flexible and adaptable to evolving project deliverables and business priorities

Principal Duties and Responsibilities :

Design, develop, and maintain scalable

ETL pipelines

using

SSIS and / or Azure Data Factory

Develop complex SQL queries, stored procedures , views, and user-defined functions

Build and maintain SSAS models (Tabular / Multidimensional) for analytical consumption

Create interactive dashboards and reports using

Power BI

Collaborate with business analysts and data stakeholders to gather and translate requirements into data solutions

Participate in all phases of the BI solution lifecycle, from design and development to testing and deployment

Monitor and troubleshoot BI and ETL processes; identify performance bottlenecks and implement solutions

Follow best practices in development, code reviews, testing, and documentation

Stay current with new tools and technologies in the data ecosystem

Adhere to enterprise data governance, privacy, and security standards