Contract
Role: Databricks Engineer
Role: Databricks Engineer
Location: Atlanta, GA (Hybrid)
Role Summary:
Databricks Engineer with analytical expertise to design, develop, and optimize scalable data pipelines and analytics solutions using the Databricks platform. Closely with data scientists, analysts, and business stakeholders to transform raw data into actionable insights that drive strategic decision-making.
Databricks Engineer with analytical expertise to design, develop, and optimize scalable data pipelines and analytics solutions using the Databricks platform. Closely with data scientists, analysts, and business stakeholders to transform raw data into actionable insights that drive strategic decision-making.
Required Skills:
• Proficiency in Databricks, Apache Spark, Pyspark and Azure data platforms.
• Strong analytical and problem-solving skills with experience in data wrangling and visualization.
• Expertise in SQL, Python, and data modeling techniques.
• Familiarity with Delta Lake, ML flow, and notebook-based development.
• Ability to interpret complex datasets and communicate insights effectively.
• Strong analytical and problem-solving skills with experience in data wrangling and visualization.
• Expertise in SQL, Python, and data modeling techniques.
• Familiarity with Delta Lake, ML flow, and notebook-based development.
• Ability to interpret complex datasets and communicate insights effectively.
Key Responsibilities:
• Develop and maintain robust ETL/ELT pipelines using Apache Spark, Pyspark on Databricks.
• Collaborate with cross-functional teams to understand data requirements and deliver analytical solutions.
• Implement data quality checks, performance tuning, and scalable data models.
• Leverage SQL, Python, and Spark to perform advanced data analysis and reporting.
• Monitor and troubleshoot data workflows to ensure reliability and accuracy.
• Develop and maintain robust ETL/ELT pipelines using Apache Spark, Pyspark on Databricks.
• Collaborate with cross-functional teams to understand data requirements and deliver analytical solutions.
• Implement data quality checks, performance tuning, and scalable data models.
• Leverage SQL, Python, and Spark to perform advanced data analysis and reporting.
• Monitor and troubleshoot data workflows to ensure reliability and accuracy.
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