Azure Data Engineer: Build Scalable ELT Pipelines

Ethereum Technologies; Austin (TX); On-site; USD 90,000 - 130,000; Full time

Job summary

Ethereum Technologies in Austin is seeking a skilled data engineer to design and optimize Azure-based ETL/ELT pipelines. You will work with Azure Data Factory, Databricks, PySpark, and SQL to transform data from multiple sources into scalable lakehouse solutions.

The role requires hands-on experience with ADLS Gen2, Delta Lake, and CI/CD practices, collaborating with data teams and stakeholders to ensure data quality and governance.

Qualifications

• Strong experience with Azure cloud data services and data pipelines.
• Hands-on with ADF and Databricks for ETL/ELT design.
• Proficient in Python, PySpark and SQL optimization.
• Experience with ADLS Gen2, Synapse Analytics, and data modeling.
• Familiar with CI/CD pipelines and data security/governance basics.
• Knowledge of Delta Lake and scalable data lake/warehouse design.

Responsibilities

• Design, develop, and maintain scalable ETL/ELT pipelines using ADF.
• Build and optimize data processing with Azure Databricks and PySpark.
• Develop data transformation workflows using Python and SQL.
• Ingest data from databases, APIs, files, and cloud platforms.
• Build data lake and data warehouse solutions with ADLS Gen2 and Synapse.
• Tune Spark jobs and SQL for performance; implement data quality checks.
• Collaborate with data architects and stakeholders; enable CI/CD deployment.
• Ensure data security, governance, and compliance across pipelines.

Skills

Azure cloud data services

Azure Data Factory (ADF)

Azure Databricks

Python

PySpark

SQL

Delta Lake

Azure Synapse Analytics

ADLS Gen2

CI/CD

Tools

Azure DevOps

Git

Delta Lake

Job description

Ethereum Technologies in Austin is seeking a skilled data engineer to design and optimize Azure-based ETL/ELT pipelines. You will work with Azure Data Factory, Databricks, PySpark, and SQL to transform data from multiple sources into scalable lakehouse solutions.

The role requires hands-on experience with ADLS Gen2, Delta Lake, and CI/CD practices, collaborating with data teams and stakeholders to ensure data quality and governance.