Finance Data & AI Automation Engineer

Кипр

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

Навыки

Обновлено 30 июля