Компания не указана
Finance Data & AI Automation Engineer
1 мес. назад
B2
sqlmicrosoft fabricazure data factorysynapserest apigitpythonpower bi
Looking for a Data & AI Automation Engineer to join IT team to transform financial data management using Microsoft Fabric and AI automation.
Responsibilities
- 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
- 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)
- 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
- 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