Microsoft Azure Fabric - Senior Data Engineer IN
Pune, Maharashtra, IN
Description
Sr Data Engineers & Tech Leads – Azure / Microsoft Fabric
Department: Sales and Delivery Team - Empower
Industry: Information Technology & Services, Computer Software, Management Consulting
Location: WFH/ India Remote
Experience Range: 5 - 10 years
Basic Qualification: Bachelor of Engineering or Equivalent
Travel Requirements: Not required
Website: www.exusia.com
Exusia, a cutting-edge digital transformation consultancy, and is looking for top talent in Data Engineering space with specific skills in Azure / Microsoft Fabric to join our global delivery team's Data Engineering practice in India.
What’s the Role?
Full-time job to work with Exusia's clients to design, develop and maintain large scale data engineering solutions. The right candidates will also get a chance to work across the entire data landscape apart from data engineering including Data Governance & Reporting & Visualization. The role will provide an opportunity to work closely with client stakeholders to capture the requirements, design and implement end to end data analytics solutions.
Criteria for the Role!
· Have a minimum of 5 years’ experience in Data management, Data engineering & Data governance space
· At least 3 years in a hands-on role using Azure services relevant to data engineering & Analytics and worked on at least 1 project on Microsoft Fabric
· Should have worked on large data initiatives and should have exposure to cloud hosted DWH & Data lakes
· Education Qualification – Bachelor of Science (preferably in Computer and Information Sciences or Business Information Technology) or an Engineering degree in the above areas
Requirements
Key Responsibilities:
Work with business stakeholders to gather and analyze business requirements, building a solid understanding of the Data Analytics and Data Governance domain
Document, discuss and resolve business, data and reporting issues within the team, across functional teams, and with business stakeholders
- Should be able to work independently and come up with solution design
- Build optimized data processing solutions using the given toolset
- Provide hands on technical leadership and work on multiple projects if required
- Design pipelines to ingest & integrate structured/semi structured and unstructured data from heterogeneous sources
- Collaborate with delivery leadership to deliver projects on time adhering to the quality standards
- Contribute to talent recruitment, competency building and providing mentor-ship to junior resources for these skills
Mandatory Skills:
- Strong DWH and ETL conceptual knowledge
- Experience using various components of Microsoft Fabric for storage, Data ingestion and processing, Data governance & reporting
- Design data solutions and data models using Onelake to support DWH, Data Lake and Lakehouse architecture
- Data ingestion for batch & streaming data using Data Factory/ Fabric & Databricks
- Orchestration of data ingestion pipelines using Data Factory or other Azure services
- Hands on experience using Azure purview for governing data assets including Metadata, Data Catalog & Data lineage
- Hands on experience using Azure SQL Database, Azure Analysis Services and Synapse Analytics
- Specific exposure to Microsoft accelerators such as
- Microsoft Fabric Toolbox
- Metadata-Driven Ingestion & Processing
- Experience working with multiple source databases
- Data migration experience from legacy databases or other cloud ecosystems to Microsoft Fabric
- Experience is Spark / Pyspark with some hands on with Databricks is highly desired
Nice-to-Have Skills
· Provisioning and managing Fabric environment
· Knowledge of any other relevant Azure data engineering services
· Building and managing PowerBI models on top of Fabric
· Exposure to building low code / No code data centric apps using Power Apps
· Integrate Power Platform components with Azure based services
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Architecture Azure Consulting Data Analytics Databricks Data governance Data management Engineering ETL Pipelines Power BI PySpark Spark SQL Streaming Unstructured data
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