Job Description Data Engineer (Databricks)
Level: Mid-level
Experience: 5 7 years
Employment Type: Contract
Shift Time: PST time Zone
About the Role
We are seeking a skilled Data Engineer with 5 7 years of experience to join our data engineering team. The ideal candidate will have strong hands-on experience building and optimizing scalable ETL pipelines using PySpark and Databricks. This role requires solid problem-solving skills, a performance-driven mindset, and the ability to collaborate effectively with both technical and non-technical stakeholders.
Key Responsibilities
Design, develop, and maintain scalable ETL pipelines for large-scale data processing.
Build and optimize data transformations using PySpark (intermediate to advanced) and Databricks.
Ensure high performance, scalability, reliability, and cost efficiency of data pipelines.
Collaborate with cross-functional teams to gather requirements and deliver robust data solutions.
Troubleshoot, debug, and resolve issues related to data processing and pipeline failures.
Implement best practices for data quality, governance, monitoring, and performance tuning.
Must-Have Skills
5 7 years of hands-on experience in Data Engineering.
Strong proficiency in PySpark (intermediate to advanced level).
Proven hands-on experience with Databricks.
Strong understanding of ETL processes, data transformations, and pipeline orchestration.
Experience in performance optimization for large-scale data pipelines.
Excellent analytical, problem-solving, and communication skills.
Good-to-Have Skills
Experience working with cloud platforms such as AWS or Google Cloud Platform.
Knowledge of modern data architectures, including data lakes and data warehouses.
Exposure to CI/CD pipelines for data engineering workflows.
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