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Senior Data Warehouse Engineer

Remote:

Full Remote

Experience:

Senior (5-10 years)

Work from:

India

Offer summary

Qualifications:

8-10 years of experience in data warehousing, Proficiency in Power BI Fabric and Power Apps, Strong expertise in Microsoft SQL Server and related tools, Hands-on experience with Python for data automation.

Key responsabilities:

Design and implement business intelligence solutions
Develop scalable data warehouse solutions

AviinTech Business Solutions SME https://www.aviintech.com/

11 - 50 Employees

See all jobs

Job description

Experience: 8-10 Years

Location: Remote

Employment Type: Full-time

Key Responsibilities:

Design, develop, and implement business intelligence solutions using Power BI Fabric.
Create and deploy Power Apps solutions based on business requirements.
Develop scalable and efficient data warehouse solutions using Microsoft SQL Server and related tools.
Design and maintain ETL processes using SQL Server Integration Services (SSIS) to extract, transform, and load data from various sources.
Optimize data models and schema structures using Microsoft SQL Server Analysis Services (SSAS) for analytical reporting and business intelligence.
Develop high-quality Python scripts for data processing and automation, utilizing relevant libraries and frameworks.
Implement and manage cloud-based data warehouse solutions using Microsoft Azure (Azure SQL Database, Azure Data Factory) and AWS (Redshift, Glue).
Work with big data technologies such as Data Lake, Apache Spark, or similar frameworks for large-scale data processing and analytics.
Collaborate with cross-functional teams to understand business needs and translate them into technical solutions.
Ensure data security, integrity, and compliance with industry best practices.

Required Skills & Qualifications:

8-10 years of experience in data warehousing, ETL development, and business intelligence solutions.
Proficiency in Power BI Fabric and Power Apps for dashboarding and reporting.
Strong expertise in Microsoft SQL Server, SSIS, SSAS, and database modeling.
Hands-on experience with Python for data manipulation and automation.
Experience with Azure (Azure SQL, Data Factory) and AWS (Redshift, Glue) cloud services.
Knowledge of big data technologies like Data Lake, Apache Spark, or similar tools.
Excellent problem-solving and analytical skills.
Strong communication and collaboration abilities to work with stakeholders.

Preferred Qualifications:

Certification in Azure Data Engineer, AWS Data Analytics, or Power BI.
Experience with machine learning models and AI-driven analytics is a plus.
cloud technologies are advantageous.