Senior Databricks Data Engineer - Trading Data Pipelines

Ethereum Technologies LLC; New York (NY); On-site; USD 140,000 - 190,000; Full time

Job summary

ETHEREUM TECHNOLOGIES LLC is seeking a senior data engineer to manage and support batch processes, data pipelines in Azure Databricks and Azure Data Factory, and Bloomberg market data feeds within trading platforms.

You will monitor, troubleshoot, and optimize ETL pipelines using Python, Spark, and SQL, and collaborate with operations, support, and infrastructure teams to improve data workflows.

10+ years in financial services data engineering or production support are required.

Qualifications

• 10+ years of experience in data engineering or production support within financial services or trading environments.
• Hands-on experience with Azure Databricks, Azure Data Factory, and Azure Storage, Logic Apps, Fabric.
• Strong Python and SQL programming skills.
• Experience with Bloomberg data feeds (BPIPE, TSIP,SFTP).

Responsibilities

• Manage and support batch processes and data pipelines in Azure Databricks and Azure Data Factory.
• Integrate and process Bloomberg market data feeds and files into trading or analytics platforms.
• Monitor, troubleshoot, and resolve data and system issues related to trading applications and market data ingestion.
• Develop, automate, and optimize ETL pipelines using Python, Spark, and SQL.
• Manage FTP/SFTP file transfers between internal systems and external vendors.
• Ensure data quality, completeness, and timeliness for downstream trading and reporting systems.
• Collaborate with operations, application support, and infrastructure teams to resolve incidents and enhance data workflows.

Skills

Python

SQL

Tools

Azure Databricks

Azure Data Factory

Azure Storage

Logic Apps

Fabric

Bloomberg data feeds

Job description

ETHEREUM TECHNOLOGIES LLC is seeking a senior data engineer to manage and support batch processes, data pipelines in Azure Databricks and Azure Data Factory, and Bloomberg market data feeds within trading platforms.

You will monitor, troubleshoot, and optimize ETL pipelines using Python, Spark, and SQL, and collaborate with operations, support, and infrastructure teams to improve data workflows.

10+ years in financial services data engineering or production support are required.