Data Engineer / Support Analyst

Job Summary:
We are seeking an experienced Data Engineer / Support Analyst with strong expertise in Databricks, Azure cloud services, Bloomberg terminal and BBG data integration, and batch job support. The ideal candidate will have a background in financial markets, with hands-on experience managing data pipelines, FTP file transfers, and real-time/batch processing in a production environment.

Key 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 analytics platforms.
* Monitor, troubleshoot, and resolve data and system issues related to 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 reporting systems.
* Collaborate with desks, application support, and infrastructure teams to resolve incidents and enhance data workflows.
* Provide L2/L3 production support for critical market data systems.

Required Skills & Experience:
* 10+ years of experience in data engineering or production support within financial services.
* 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, B-Quant).

* Experience with Git, CI/CD pipelines, and Azure DevOps.
* Proven ability to support batch jobs, troubleshoot failures, and manage job scheduling.
* Experience handling FTP/SFTP file transfers and automation (e.g., using scripts or managed file transfer tools).
* Solid understanding of market data concepts, and financial instruments.
* Excellent communication, problem-solving, and stakeholder management skills.

Nice to Have:
* Experience with Power BI or other visualization tools.
* Familiarity with Kafka, Event Hubs, or real-time streaming architectures.
* Knowledge of ITIL / incident management best practices.

* Knowledge of building AI Agents and LLMs