Business Intelligence Data Engineer at HFM, transforming raw data into analytics-ready datasets. Bridging data engineering and analysis for strategic insights in a global trading firm.
Responsibilities
Design, develop, and optimize data models to support analytics, reporting, and machine learning workflows, ensuring seamless integration with BI infrastructure.
Utilize SQL and Python to clean, process, and analyze large datasets efficiently, supporting both analytics and machine learning processes.
Develop, optimize, and maintain ETL pipelines for seamless data extraction, transformation, and integration.
Perform exploratory data analysis to identify trends, patterns, and insights that inform strategic initiatives, while assisting in preprocessing and transforming data for machine learning models.
Develop advanced DAX measures for business calculations, optimize report performance, and enhance analytical capabilities in Power BI.
Create interactive dashboards and visualizations in Power BI, incorporating KPIs, business calculations, and data aggregations.
Support the integration and deployment of data science models into BI workflows, ensuring smooth data flow and system scalability.
Ensure data governance, integrity, consistency and scalability to support data quality, security, and compliance across all models including those used for machine learning and analytics.
Define and manage role-based access controls to protect sensitive data and ensure appropriate user access.
Work closely with data engineering teams to improve data models, processing workflows, and overall infrastructure.
Collaborate with data scientists, analysts, and business stakeholders to translate data insights into actionable business strategies.
Create and maintain technical documentation for BI models, queries, and processes.
Train business users on BI tools, best practices, and data-driven decision-making.
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 for performance and scalability.
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.
Ability to collaborate with business stakeholders and technical teams to translate requirements into data-driven solutions.
Strong problem-solving skills and critical thinking abilities.
Excellent command of the English language.
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!)
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