Vacancy description
TalentBridge
India, India
Data Engineers required ASAP in India, India is listed on Jobeax. Browse 30,000+ vacancies available.
CONTRACT TO HIRE ( 6 MONTHS OF CONTRACT THEN WILL CONVERT TO FULL TIME ) NEED ASAP ( START DATE 1st September)
Data Engineer
About the Role:
As a Data Engineer, you'll design, build, and scale the data systems that analysts, business leaders, and products rely on every day. You'll work at the intersection of engineering and real business impact, turning raw data into something reliable, fast, and meaningful.
Key Responsibilities:
Data Architecture and Design:
Design scalable, reliable, and secure data solutions that meet real business needs
Develop data models, data flows, and integration architectures from the ground up
Own the full lifecycle — from requirements gathering to production deployment
Ensure solutions meet business requirements and align with best practices.
Data Ingestion and Integration:
Build and manage data pipelines to ingest data from various sources, including third-party and RESTful APIs.
Build ETL/ELT processes using ADF, Fabric Data Flows , and Notebooks.
Embed MDM solutions into pipelines, ensuring seamless data sync across systems.
Data Storage and Management:
Design and implement data storage solutions using Microsoft Fabric , Azure SQL Database, and Azure Delta Lake.
Define match, merge, and survivorship rules for master data management and ensure platform integration with other systems.
Data Transformation and Processing:
Use Python, PySpark, and Fabric Notebooks to process and transform data at scale.
Implement transformation logic to prepare data for analysis and reporting.
Optimize data processing workflows for efficiency and scalability.
Analytics and Reporting:
Design and develop SSAS OLAP cubes, tabular & semantic models to support complex analytical queries and reporting.
Define dimensions, hierarchies, and measures; write MDX and DAX queries to retrieve and manipulate data.
Integrate models with reporting tools such as Power BI, Excel, etc. to deliver dashboards and insights.
Data Quality:
Implement data quality checks, validation processes, and monitoring to ensure accuracy and consistency.
Maintain compliance with data governance policies across the full data lifecycle.
Monitoring and Optimization:
Monitor data solutions for performance, reliability, and scalability; troubleshoot and resolve issues promptly.
Optimize query and price performance through indexing and partitioning strategies.
Security:
~ Implement role-based access control, auditing, and encryption to protect data assets.
Documentation and Training:
Document data architectures, processes, and procedures.
Provide training and support to team members and end-users.
Qualifications:
Core Skills:
Python + SQL: Strong Python and SQL proficiency, including advanced queries and query optimization.
Big Data: Apache Spark / PySpark for large-scale distributed data processing.
Data Pipelines: Building ETL/ELT pipelines using Azure Data Factory, Fabric Data Flows, and Fabric Notebooks.
Cloud + Warehouse: Hands-on experience with Microsoft Azure services and Microsoft Fabric for cloud data warehousing and lakehouse architecture.
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