azure data engineer with fabric ASV Consulting Services

6.0 - 10.0 years

8 - 12 Lacs

Pune, Gurugram, Bengaluru

Work from Office

Contractual Hiring manager :- My profile :- linkedin.com/in/yashsharma1608 Payroll of :- https://www.nyxtech.in/ 1. AZURE DATA ENGINEER WITH FABRIC The Role : Lead Data Engineer PAYROLL Client - Brillio About Role: Experience 6 to 8yrs Location- Bangalore , Hyderabad , Pune , Chennai , Gurgaon (Hyderabad is preferred) Notice- 15 days / 30 days. Budget -15 LPA AZURE FABRIC EXP MANDATE Skills : Azure Onelake, datapipeline , Apache Spark , ETL , Datafactory , Azure Fabric , SQL , Python/Scala. Key Responsibilities: Data Pipeline Development: Lead the design, development, and deployment of data pipelines using Azure OneLake, Azure Data Factory, and Apache Spark, ensuring efficient, scalable, and secure data movement across systems. ETL Architecture: Architect and implement ETL (Extract, Transform, Load) workflows, optimizing the process for data ingestion, transformation, and storage in the cloud. Data Integration: Build and manage data integration solutions that connect multiple data sources (structured and unstructured) into a cohesive data ecosystem. Use SQL, Python, Scala, and R to manipulate and process large datasets. Azure OneLake Expertise: Leverage Azure OneLake and Azure Synapse Analytics to design and implement scalable data storage and analytics solutions that support big data processing and analysis. Collaboration with Teams: Work closely with Data Scientists, Data Analysts, and BI Engineers to ensure that the data infrastructure supports analytical needs and is optimized for performance and accuracy. Performance Optimization: Monitor, troubleshoot, and optimize data pipeline performance to ensure high availability, fast processing, and minimal downtime. Data Governance & Security: Implement best practices for data governance, data security, and compliance within the Azure ecosystem, ensuring data privacy and protection. Leadership & Mentorship: Lead and mentor a team of data engineers, promoting a collaborative and high-performance team culture. Oversee code reviews, design decisions, and the implementation of new technologies. Automation & Monitoring: Automate data engineering workflows, job scheduling, and monitoring to ensure smooth operations. Use tools like Azure DevOps, Airflow, and other relevant platforms for automation and orchestration. Documentation & Best Practices: Document data pipeline architecture, data models, and ETL processes, and contribute to the establishment of engineering best practices, standards, and guidelines. C Innovation: Stay current with industry trends and emerging technologies in data engineering, cloud computing, and big data analytics, driving innovation within the team.C

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