PwC India
Website:
pwc.in
Company:
https://www.linkedin.com/company/pwc-india
Seniority: Mid-Senior level
Industries: IT Services and IT Consulting
Job details:
Databricks engineer Roles and Responsibilities:
Responsible for data management activities related to the migration of on-prem sources to cloud systems using Databricks architecture and solutions. In this role, you will be responsible for the development and maintenance of data pipelines and analytics solutions in a cloud-based environment.
Desired Candidate Profile:
-Minimum 4 years of professional experience with working knowledge in a Data and Analytics role with a Global organization
-4 to 8 years of experience in working with Databricks tech stacks
-Experience in leading development of Data and Analytics products, from Requirement Gathering State to Driving User Adoption
-Develop and optimize ETL processes using Databricks and related tools like Apache Spark
-Design efficient data processing systems and pipelines using Databricks, APIs, and other cloud services
-Candidate with strong data transformation experience on Unity Catalog, Delta Tables, DLT
-Strong proficiency in writing and optimizing SQL queries and working with databases
-Ability to acquire specialized domain knowledge required to be more effective in all work activities
-BI & Data-warehousing concepts are a must.
-Design, develop, and maintain scalable ETL/ELT pipelines using PySpark on Databricks.
-Ingest and transform data from multiple structured and unstructured sources including cloud storage (Azure Data Lake, AWS S3, etc.).
-Optimize Spark jobs for performance and cost-efficiency on the Databricks platform.
-Collaborate with data scientists, analysts, and stakeholders to understand data requirements and deliver high-quality solutions.
-Implement best practices in data engineering, including modular coding, unit testing, and version control (e.g., Git).
-Automate data workflows and schedule jobs using Databricks Workflows or external orchestration tools (e.g., Airflow, Azure Data Factory).
-Ensure data quality, integrity, and governance in all data pipelines.
-Participate in code reviews, performance tuning, and system monitoring.
-Document solutions, processes, and configurations.
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