PySpark Developer

1 day ago

Hyderabad Bengaluru Chennai, India Coders Brain Technology Private Limited Full time

Job Description

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:

7+ years of experience in data engineering or distributed systems development.

Strong programming skills in Python and PySpark.(7+ years)

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 Bachelor's 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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