Reporting to the Senior Data \& Insights Manager, the Data Engineer will be a key contributor to the migration of the company’s reporting platform, focusing on back-end systems and data infrastructure. This role is responsible for ensuring the smooth integration and processing of large-scale data, building robust data pipelines, and creating scalable data products to support multiple applications across the company. The Data Engineer will collaborate with various departments to implement and maintain high-performance data systems that empower business users with actionable insights. Responsibilities also include optimizing data workflows, driving innovation in data engineering processes, and ensuring data integrity throughout the platform migration.
Main responsibilities:
Collaboration
: Partner with cross-functional teams to understand their data needs and design solutions that streamline data flows and integration across multiple applications.
Semantic Model \& KPI Definitions:
Build and maintain a comprehensive semantic model, working closely with stakeholders to define and standardize KPIs that align with business objectives and reporting requirements.
Platform Migration:
help with back-end migration efforts, ensuring that all data pipelines, storage solutions, and processing systems are transitioned efficiently and without disruption to business operations.
Data Pipeline Development
: Design, build, and maintain scalable and efficient data pipelines that ensure accurate and timely data delivery to support business intelligence tools and applications.
System Optimization:
Continuously optimize and monitor back-end systems, databases, and data workflows to maintain high performance and cost-efficiency.
Data Integration:
Ensure seamless integration of data from various sources into centralized platforms, enabling comprehensive reporting and analysis capabilities.
Problem-Solving:
Leverage data engineering expertise to troubleshoot issues, optimize performance, and solve complex challenges related to data storage, processing, and accessibility.
Innovation \& Collaboration:
Work closely with the Data \& IT teams to explore new technologies and methodologies, driving innovation in the company’s data engineering practices and supporting evolving business needs.
Requirements:
Must have
University Degree (Data Engineering, Information Systems, or a related field)
3+ years in a data engineering or similar role, with demonstrated success in supporting data transformation and migration projects, ideally from legacy systems to modern data platforms
Proven track record in supporting data transformation projects, nice to have would be migrating from legacy systems to modern BI tools like Power BI
Technical Skills:
Data Transformation: Strong experience in ETL/ELT processes, data modeling, and reporting in Microsoft environment (SSIS, Azure DataFactory, Synapse, Fabric)
Power BI Semantic Model: Proven ability to create and maintain a comprehensive analytical data models, specifically in Power BI and/or Microsoft SQL Server Analysis Services (SSAS), including KPI definitions and metric standardization to meet reporting requirements
SQL Proficiency: Proficient in SQL (any dialect) for data manipulation, transformation, and analysis.
DAX Proficiency: Proficient in DAX language for Analysis Services/Power BI.
Data Pipelines: Experience building and optimizing data pipelines for large-scale data processing.
Cloud Experience: Familiarity with cloud environments such as Azure, with a focus on tools like Synapse Analytics
Ability to analyze both structured and unstructured data, with a proactive approach to identifying and solving data issues
Effective communication skills to collaborate with stakeholders across departments, strong problem-solving abilities, and a commitment to data quality and accuracy
English at business level
Nice to have
Experience with SSRS and SSIS, or similar reporting and integration tools
Hands-on experience with BI tools like Power BI, with a strong understanding of KPI definitions and dashboard creation