Azure Databricks Data Engineer - Lakehouse & Pipelines

Ethereum Technologies; Dallas (TX); On-site; USD 120,000 - 160,000; Full time

Job summary

Ethereum Technologies in Dallas, TX seeks an experienced Azure Databricks Engineer to design, build, and optimize large-scale data pipelines and lakehouse architectures using Azure Databricks, PySpark, and Spark SQL. You will work with Azure Data Factory, ADLS Gen2, and Delta Lake, implement CI/CD, model data, and collaborate with architects and analysts to deliver scalable, cost-efficient data solutions.

The role requires hands-on development, performance tuning, data quality checks, and close

Qualifications

• Minimum hands-on experience with Azure Databricks and Spark.
• Strong Python and SQL data warehousing knowledge.
• Experience building scalable data pipelines and lakehouse architectures.
• Familiarity with ADF, ADLS Gen2, and Delta Lake.
• Experience with CI/CD and DevOps practices.

Responsibilities

• Design, develop, and optimize scalable data pipelines on Azure Databricks.
• Implement ETL/ELT workflows using PySpark and Spark SQL.
• Tune Spark jobs for performance and cost efficiency.
• Develop data models, integrations, and migrations.
• Collaborate with stakeholders and implement CI/CD deployment processes.
• Apply data quality checks, monitoring, and error handling.

Skills

Python

Spark

SQL

Data Warehousing

ETL/ELT

Data Modeling

Performance Tuning

Data Governance

CI/CD

Tools

Azure Databricks

PySpark

Spark SQL

Azure Data Factory

Azure Data Lake Storage Gen2

Delta Lake

Azure DevOps

Terraform

Kafka

Event Hubs

Azure Synapse Analytics

Job description

Ethereum Technologies in Dallas, TX seeks an experienced Azure Databricks Engineer to design, build, and optimize large-scale data pipelines and lakehouse architectures using Azure Databricks, PySpark, and Spark SQL. You will work with Azure Data Factory, ADLS Gen2, and Delta Lake, implement CI/CD, model data, and collaborate with architects and analysts to deliver scalable, cost-efficient data solutions.

The role requires hands-on development, performance tuning, data quality checks, and close