Finance Data & AI Automation Engineer

Location: Cyprus (office), full-time

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

Skills

• SQL
• Microsoft Fabric
• Azure Data Factory
• Synapse
• REST APIs
• Git
• Python
• Azure Functions
• Logic Apps
• App Service
• Power BI
• DAX
• Power Automate