Finance Data & AI Automation Engineer (Fintech)

#vacancy.
Finance Data & AI Automation Engineer
Financial Data Platform · MS Fabric
 
 
About the Role
We're looking for a Data & AI Automation Engineer to join our IT team and transform how we manage financial data. You'll work at the intersection of data engineering, AI, and finance — building tools that let our team manage a Microsoft Fabric data warehouse through natural language instead of manual clicks.
 
This isn't a typical data engineering role. You'll take over day-to-day DWH operations, then systematically automate them — building AI agents that handle pipeline orchestration, account mapping, budget processing, and data quality monitoring. The end goal: a platform where the Data Lead manages everything through a chat interface, with zero manual routine.
 
What You'll Do
 
DWH Operations & Financial Data
•       Own the day-to-day operation of financial data pipelines in Microsoft Fabric — monitoring, troubleshooting, refreshing
•       Validate data quality at each period close: completeness, mapping accuracy, reconciliation with source systems
•       Maintain and update account mapping files (GL accounts, projects, cost centers) in coordination with the Finance team
•       Manage SSAS model refreshes on Azure Analysis Services for Excel and Power BI consumers
•       Onboard new country entities into the DWH by replicating existing pipeline patterns
•       Support the budget cycle: template preparation, data loading, model updates during high-frequency budget seasons
 
AI Agents & Automation
•       Design and build a chat-based agent (Teams bot) that allows the Data Lead to manage DWH operations through natural language commands — refresh pipelines, check status, investigate failures
•       Train the agent on our specific Fabric environment: workspace structure, pipeline names, dataset relationships, SSAS models
•       Build an automated mapping workflow: detect unmapped accounts → AI suggests correct P&L/BS classification → notify Finance via Teams → apply confirmed mapping → refresh data
•       Automate budget template generation based on current chart of accounts and prior year actuals
•       Build file-watch automation that detects budget file updates and auto-refreshes Fabric pipelines and SSAS models
•       Implement automated data quality checks with proactive alerts to Teams (anomalies, missing data, freshness issues)
 
Documentation & Process
•       Document all DWH processes, data flows, mapping logic, and transformation rules
•       Maintain a data dictionary for financial datasets
•       Version-control all automation code, agent prompts, and configurations
•       Create runbooks for incident response and pipeline recovery
 
Requirements
 
Must Have
•       SQL — confident (complex queries, data validation, stored procedures)
•       Strong attention to detail — you'll be catching data errors before they reach reports
•       Microsoft Fabric, Azure Data Factory, or Synapse — hands-on experience with data pipelines
•       API integration — comfortable working with REST APIs (Fabric API, SSAS API, Teams API)
•       Experience building bots, automation workflows, or scheduled jobs
•       Git — version control for code and configurations
•       English, Russian — professional working proficiency
 
Nice to Have
•       LLM / AI agent development
•       Python — working level (API integration, scripting, data manipulation)
•       Azure cloud — Functions, Logic Apps, or App Service
•       Power BI / DAX — understanding the reporting layer our users interact with
•       Financial domain knowledge — P&L, Balance Sheet, budgeting, period close processes
•       Power Automate / Logic Apps — for file monitoring and Teams integration
•       Azure Analysis Services (SSAS) — model processing and management
•       ERP experience (1C, SAP, Oracle) — understanding source systems

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