We are searching for Professionals below business requirements for one of our clients. Please read through the requirements and connect with us in case it suits your profile.
Job Description –
· Extensive experience in designing, implementing, and supporting Data Warehousing, ETL and Business Intelligence solutions on Microsoft Fabric data pipelines
· Design and implement scalable and efficient data pipelines using Azure Data Factory, Pyspark notebooks, Spark SQL, and Python. This includes data ingestion, data transformation, and data loading processes.
· Create and optimize data models to support business intelligence and analytics requirements.
· Develop complex SQL scripts and procedures for data extraction, transformation, and loading.
· Collaborate with business team to understand data requirements and translate them into technical specifications.
Implementation and Maintenance
· Implement data integration solutions, ensuring data quality, consistency, and security.
· Monitor and troubleshoot ETL processes, identifying and resolving issues in a timely manner.
· Maintain and optimize ETL pipelines for performance and scalability.
· Ensure data compliance and governance standards are met throughout the ETL process.
· Collaboration and Communication
· Work closely with cross-functional teams including data analysts, and business stakeholders.
· Document ETL processes, data flows, and technical specifications for future reference and knowledge sharing.
· Communicate effectively with stakeholders to ensure alignment on project goals and deliverables.
Education, Experience and Skills
· Bachelor’s degree in Computer Science, Information Technology, or a related field.
· At least 10+ years of experience in ETL development, data integration, or related roles.
· Proven experience with Microsoft Fabric and other Microsoft data integration tools.
· Strong knowledge of SQL, data modeling, and data warehousing concepts.
· Proficient in Microsoft Fabric tools and environments.
· Advanced SQL scripting and database management skills.
· Strong problem-solving and analytical skills.
· Detail-oriented with a focus on data quality and accuracy.
· Familiarity with Agile development methodologies