TL;DR

Analytics Engineer (Business Intelligence, ML): Designing, developing, and optimizing data models and ETL pipelines for analytics, reporting, and machine learning workflows, with an accent on seamless integration with BI infrastructure and data governance. Focus on utilizing SQL, Python, and Power BI for efficient data processing, analysis, and visualization, ensuring data integrity and scalability in the FX industry.

Location: Hybrid in Larnaca, Cyprus (up to 2 days working from home)

Company

%hirify_global% is an internationally acclaimed multi-asset broker, delivering cutting-edge trading tools, platforms, and conditions to traders worldwide.

What you will do

Design, develop, and optimize data models to support analytics, reporting, and machine learning workflows.
Utilize SQL and Python to clean, process, and analyze large datasets efficiently.
Develop, optimize, and maintain ETL pipelines for seamless data extraction, transformation, and integration.
Create interactive dashboards and visualizations, and develop advanced DAX measures in Power BI.
Support the integration and deployment of data science models into BI workflows.
Ensure data governance, integrity, consistency, and scalability across all models.

Requirements

University degree in Computer Science, Data Science, or a related field.
Minimum of 3 years of experience in designing, developing, and implementing data solutions.
Previous experience in the FX industry is required.
Proficiency in SQL scripting, with expertise in optimizing complex SQL queries.
Strong skills in designing and implementing data models (e.g., star or snowflake schemas) for BI applications.
Proficiency in Power BI for developing interactive reports, dashboards, and data visualizations.
Advanced skills in DAX for creating business calculations, measures, and KPIs in Power BI.
Solid experience in Python for data analysis, machine learning, and automation of data workflows.
Excellent command of the English language.

Nice to have

Experience in developing ETL pipelines for data integration and transformation.
Knowledge of data science projects related to customer analysis, behavior prediction, and segmentation.
Familiarity with SQL Server Analysis Services for OLAP modelling.
Experience with version control systems for managing BI reports, scripts, or development work.
Knowledge of Microsoft Fabric Cloud Services for cloud-based data solutions.

Culture & Benefits

Hybrid Work Model (up to 2 days working from home).
22 days of Annual Leave (reaching up to 30 days per year based on years’ service).
Comprehensive Health & Life Insurance (from day one!).
Friday afternoons off in Summer (July & August).
Birthday Leave.
Gym Membership (Larnaca).
Referral Bonus.
Paid Time Off for Training & Education.