
Profile: Big Data Engineer (System Design)
Experience: 5+ years
Location: Bangalore
Work Mode: Hybrid
About the Role
We're looking for an experienced Big Data Engineer with system design expertise to architect and build scalable data pipelines and optimize big data solutions.
Key Responsibilities
- Design, develop, and maintain data pipelines and ETL processes using Python, Hive, and Spark
- Architect scalable big data solutions with strong system design principles
- Build and optimize workflows using Apache Airflow
- Implement data modeling, integration, and warehousing solutions
- Collaborate with cross-functional teams to deliver data solutions
Must-Have Skills
- 5+ years as a Data Engineer with Python, Hive, and Spark
- Strong hands-on experience with Java
- Advanced SQL and Hadoop experience
- Expertise in Apache Airflow
- Strong understanding of data modeling, integration, and warehousing
- Experience with relational databases (PostgreSQL, MySQL)
- System design knowledge
- Excellent problem-solving and communication skills
Good to Have
- Docker and containerization experience
- Knowledge of Apache Beam, Apache Flink, or similar frameworks
- Cloud platform experience.

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Candidate Profile:
You have:
- Experience in working with Selenium (Java or any other language) is MANDATORY.\
- Should have experience creating or maintaining a selenium-based framework.
- Should have worked in Agile methodology and derived modular test scripts from user stories and manual test cases.
- Should have experience with cross-browser testing using Selenium Grid.
- You should be able to develop automation scripts and perform debugging. Also, identify common functionality and creates re-usable scripts
- You should be able to execute automated test scripts (raise and manage defects)
- Experience with other Selenium language bindings such as Javascript or Python is an added advantage.
- Experience in handling a team
Awesome to have:
- Any experience working in Healthcare Technology Education and Experience:
- Computer Science graduate
- 1-3 years of experience in Selenium with Java
- Minimum of 7 years of experience in Testing
- Solid expertise in Linux and SQL DB (Oracle / MySql)
- Knowledge of DevOps tools like GitLab, Jenkins, Jira and X-Ray
- Work experience in CICD pipeline integration and environmental set-up.
- Identification & evaluation of Automation tools/frameworks.
Job Description:
As an Azure Data Engineer, your role will involve designing, developing, and maintaining data solutions on the Azure platform. You will be responsible for building and optimizing data pipelines, ensuring data quality and reliability, and implementing data processing and transformation logic. Your expertise in Azure Databricks, Python, SQL, Azure Data Factory (ADF), PySpark, and Scala will be essential for performing the following key responsibilities:
Designing and developing data pipelines: You will design and implement scalable and efficient data pipelines using Azure Databricks, PySpark, and Scala. This includes data ingestion, data transformation, and data loading processes.
Data modeling and database design: You will design and implement data models to support efficient data storage, retrieval, and analysis. This may involve working with relational databases, data lakes, or other storage solutions on the Azure platform.
Data integration and orchestration: You will leverage Azure Data Factory (ADF) to orchestrate data integration workflows and manage data movement across various data sources and targets. This includes scheduling and monitoring data pipelines.
Data quality and governance: You will implement data quality checks, validation rules, and data governance processes to ensure data accuracy, consistency, and compliance with relevant regulations and standards.
Performance optimization: You will optimize data pipelines and queries to improve overall system performance and reduce processing time. This may involve tuning SQL queries, optimizing data transformation logic, and leveraging caching techniques.
Monitoring and troubleshooting: You will monitor data pipelines, identify performance bottlenecks, and troubleshoot issues related to data ingestion, processing, and transformation. You will work closely with cross-functional teams to resolve data-related problems.
Documentation and collaboration: You will document data pipelines, data flows, and data transformation processes. You will collaborate with data scientists, analysts, and other stakeholders to understand their data requirements and provide data engineering support.
Skills and Qualifications:
Strong experience with Azure Databricks, Python, SQL, ADF, PySpark, and Scala.
Proficiency in designing and developing data pipelines and ETL processes.
Solid understanding of data modeling concepts and database design principles.
Familiarity with data integration and orchestration using Azure Data Factory.
Knowledge of data quality management and data governance practices.
Experience with performance tuning and optimization of data pipelines.
Strong problem-solving and troubleshooting skills related to data engineering.
Excellent collaboration and communication skills to work effectively in cross-functional teams.
Understanding of cloud computing principles and experience with Azure services.
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