Responsibilities

Design, develop, and maintain scalable data pipelines and architectures using Databricks.
Collaborate with data scientists and analysts to understand data requirements and deliver high-quality data solutions.
Implement data ingestion processes from various sources, ensuring data quality and integrity.
Optimize data storage and retrieval processes for performance and cost efficiency.
Monitor and troubleshoot data pipeline performance and reliability issues.
Document data engineering processes, architectures, and best practices.
Stay updated with the latest trends and technologies in data engineering and analytics.

Mandatory Skills

Solid expertise in Databricks and its ecosystem.
Proficient in programming languages such as Python, Scala, or Java.
Experience with data modeling,



ETL processes, and data warehousing concepts.
Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and their data services.
Solid understanding of SQL and experience with relational databases.
Knowledge of big data technologies (e.g., Spark, Hadoop) is a plus.

Preferred Skills

Experience with data visualization tools (e.g., Tableau, Power BI).
Familiarity with machine learning concepts and frameworks.
Knowledge of data governance and data security best practices.
Experience with CI/CD pipelines and version control systems (e.g., Git).

Databricks

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