
PySpark Developer
2 weeks ago
Location : Chennai/Bangalore/Hyderabad/Coimbatore/ Pune
WFO : 3 days Mandatory from the above-mentioned locations.
Role Summary :
We are seeking a highly skilled PySpark Developer with hands-on experience in Databricks to join Companies IT Systems Development unit in an offshore capacity. This role focuses on designing, building, and optimizing large-scale data pipelines and processing solutions on the Databricks Unified Analytics Platform. The ideal candidate will have expertise in big data frameworks, distributed computing, and cloud platforms, with a deep understanding of Databricks architecture. This is an excellent opportunity to work with cutting-edge technologies in a dynamic, fast-paced environment.
Role Responsibilities :
Data Engineering and Processing :
- Develop and manage data pipelines using PySpark on Databricks.
- Implement ETL/ELT processes to process structured and unstructured data at scale.
- Optimize data pipelines for performance, scalability, and cost-efficiency in Databricks.
Databricks Platform Expertise :
- Experience in Perform Design, Development & Deployment using Azure Services (Data Factory, Databricks, PySpark, SQL)
- Develop and maintain scalable data pipelines and build new Data Source integrations to support increasing data volume and complexity.
- Leverage the Databricks Lakehouse architecture for advanced analytics and machine learning workflows.
- Manage Delta Lake for ACID transactions and data versioning.
- Develop notebooks and workflows for end-to-end data solutions.
Cloud Platforms and Deployment :
- Deploy and manage Databricks on Azure (e.g., Azure Databricks).
- Use Databricks Jobs, Clusters, and Workflows to orchestrate data pipelines.
- Optimize resource utilization and troubleshoot performance issues on the Databricks platform.
CI/CD and Testing :
- Build and maintain CI/CD pipelines for Databricks workflows using tools like Azure DevOps, GitHub Actions, or Jenkins.
- Write unit and integration tests for PySpark code using frameworks like Pytest or unittest.
Collaboration and Documentation :
- Work closely with data scientists, data analysts, and IT teams to deliver robust data solutions.
- Document Databricks workflows, configurations, and best practices for internal use.
Technical Qualifications :
Experience :
- 4+ years of experience in data engineering or distributed systems development.
- Strong programming skills in Python and PySpark.
- Hands-on experience with Databricks and its ecosystem, including Delta Lake and Databricks SQL.
- Knowledge of big data frameworks like Hadoop, Spark, and Kafka.
Databricks Expertise :
- Proficiency in setting up and managing Databricks Workspaces, Clusters, and Jobs.
- Familiarity with Databricks MLflow for machine learning workflows is a plus.
Cloud Platforms :
- Expertise in deploying Databricks solutions Azure (e.g., Data Lake, Synapse).
- Knowledge of Kubernetes for managing containerized workloads is advantageous.
Database Knowledge :
- Experience with both SQL (e.g., PostgreSQL, SQL Server) and NoSQL databases (e.g., MongoDB, Cosmos DB).
General Qualifications :
- Strong analytical and problem-solving skills.
- Ability to manage multiple tasks in a high-intensity, deadline-driven environment.
- Excellent communication and organizational skills.
- Experience in regulated industries like insurance is a plus.
Education Requirements :
- A Bachelors Degree in Computer Science, Data Engineering, or a related field is preferred.
- Relevant certifications in Databricks, PySpark, or cloud platforms are highly desirable.
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