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3.2

based on 415 Reviews

66 PureSoftware Jobs

Azure Data Engineer - RVN

PureSoftware

3.2

based on 415 Reviews

7-10 years

Bangalore / Bengaluru

1 vacancy

Azure Data Engineer - RVN

PureSoftware

posted 1mon ago

Job Role Insights

Flexible timing

Key skills for the job

Data Analytics Python Automation Testing SAP Business Intelligence Apache Nifi Data Modeling

+ 4 more

Job Description

Key Responsibilities:

Data Pipeline Development: Design, develop, and optimize ETL/ELT pipelines in Azure Databricks using Apache Spark , Scala , Python , and SQL for efficient data processing and transformation.
Cloud Infrastructure Management: Build and manage scalable, cloud-based data architectures and solutions using Azure Databricks , Azure Data Lake , Azure SQL Data Warehouse , and other Azure services.
Data Integration: Work closely with data scientists, analysts, and business stakeholders to integrate and process large datasets from various sources, ensuring data quality and consistency.
Optimization & Performance Tuning: Monitor and optimize performance of Databricks notebooks, jobs, and Spark clusters to ensure efficiency in both batch and stream processing.
Automation & Monitoring: Automate repetitive tasks, such as pipeline monitoring, job scheduling, and error handling using Azure DevOps , Databricks REST API , or Airflow .
Collaboration: Partner with other teams such as data science, business intelligence, and software engineering to understand data requirements and deliver solutions that enable actionable insights.
Security & Compliance: Implement and manage data security practices, ensuring compliance with industry regulations and best practices for data privacy, encryption, and access control.
Troubleshooting & Debugging: Diagnose and resolve issues with data pipelines, Databricks notebooks, and cloud infrastructure, ensuring minimal downtime and optimal performance.
Documentation: Create and maintain detailed documentation for data engineering processes, pipeline architectures, and system configurations to ensure clarity and maintainability.
Mentorship & Leadership: Provide guidance, mentoring, and technical leadership to junior engineers and data engineers, fostering knowledge sharing and improving team capabilities.

Required Skills & Qualifications:

Experience: 7+ years of experience in data engineering or a related field with a deep focus on Azure Databricks and big data technologies .
Azure Databricks Expertise: Strong hands-on experience with Azure Databricks for creating and managing Spark-based data pipelines and working with both batch and real-time data.
Programming Languages: Proficient in Python , Scala , and SQL for data processing, data transformation, and automation within Databricks environments.
Big Data Technologies: Solid understanding and experience with Apache Spark , Apache Kafka , Hadoop , and NoSQL databases (e.g., Cosmos DB , MongoDB ).
Azure Services: In-depth experience with Azure cloud services such as Azure Data Lake , Azure Data Factory , Azure SQL Database , Azure Synapse Analytics , and Azure Blob Storage .
Data Modeling & Warehousing: Familiarity with data warehousing concepts , dimensional modeling , and building and maintaining data pipelines in a cloud-based data lake architecture.
Version Control & CI/CD: Strong experience with Git , CI/CD pipelines using Azure DevOps , and infrastructure-as-code tools like ARM Templates or Terraform .
Automation & Orchestration: Experience with automating and orchestrating data workflows using tools like Apache Airflow , Azure Data Factory , or custom automation scripts.
Data Governance & Security: Solid understanding of data governance, data quality, and data security practices in the cloud environment, including role-based access control (RBAC), encryption, and auditing.
Problem-Solving & Optimization: Proven ability to optimize and troubleshoot data pipelines, Databricks notebooks, and performance bottlenecks.
Soft Skills: Strong analytical skills, problem-solving capabilities, excellent communication, and the ability to work in a team-oriented, collaborative environment.