Databricks Developer

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AI Summary

Design, develop, and optimize scalable data pipelines and analytics solutions using the Databricks platform. Collaborate with cross-functional teams to understand data requirements and deliver analytical solutions. Leverage SQL, Python, and Spark to perform advanced data analysis and reporting.

Key Highlights
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.
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.
Technical Skills Required
Databricks Datawarehouse ETL SQL Pyspark Apache Spark DevOps Databricks Engineer
Benefits & Perks
Full Remote
Contract
Nice to Have
ADF
DevOps
Databricks Engineer with analytical expertise

Job Description


Hi,

Trust you are doing well!

Please do share your resume if you are looking for this role.


Role: Databricks Developer

Location: (Full Remote)

Type: Contract


Note: F2F interview in Dallas TX for final round and the role is remote.

Must Have Skills:

Databricks

Datawarehouse

ETL

SQL

Pyspark



Nice to Have Skills:

ADF

DevOps

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.


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.


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