Manager – Data Engineering

Job Description

The Manager – Data Engineering leads the development of the next phase of the Business Intelligence and Data strategy, including data lakes, data virtualization, and modern data platforms. The role focuses on exploring new data technologies and industry trends and applying them early where they can deliver real business value. The manager also helps define key business questions, supports analysis, and develops meaningful metrics and dashboards that enable better learning and decision-making across the organization. This includes contributing to strategic documents and insights shared with senior stakeholders and internal teams.

The role is responsible for delivering reliable, enterprise-level data solutions within a large and complex data warehouse environment. This requires strong hands-on expertise in designing, building, and managing large datasets, as well as creating efficient, scalable, and cost-effective data pipelines that move data from source systems into the data warehouse and user-facing tools such as Power BI. When standard tools are not sufficient, the Data Engineering Manager is expected to design and implement custom data pipeline solutions to meet business needs.

Key Responsibilities

• Improve the performance of existing reports and analytics by applying more efficient and modern data engineering solutions.
• Work with business teams to understand BI requirements and design data models that convert raw data into meaningful insights.
• Support analysis across OLTP and OLAP systems using strong database programming skills to enable decision-making.
• Design and maintain data warehouse architecture that supports current and future business reporting needs.
• Build and maintain data lineage to improve reliability, transparency, and efficiency of the data platform.
• Develop and manage ETL infrastructure to extract data from multiple sources using SQL and big data technologies.
• Identify and implement process improvements such as automation, optimized data delivery, and scalable infrastructure design.
• Identify new data sources and build analytics solutions that support customer growth, operational efficiency, and key performance tracking.
• Own end-to-end data pipelines, including planning, data collection, transformation, and analysis.
• Create and maintain efficient data pipeline architectures capable of handling large and complex datasets.
• Ensure consistent data quality through continuous monitoring, validation, and maintenance of databases and data systems.
• Design, build, test, and deploy Power BI dashboards, including real-time data pipelines feeding reports.
• Develop ETL solutions using SSIS packages with reprocessing logic to reload historical data when required.
• Write and optimize T-SQL stored procedures, functions, triggers, indexes, and queries to automate financial and operational reporting.
• Develop SQL scripts to validate data quality, including checks for duplicates, null values, aggregation accuracy, and data inconsistencies.
• Perform detailed data quality analysis across staging, data warehouse, and data mart layers, including validation during data migration.
• Maintain logging and audit tables and implement proper error handling and monitoring within SSIS packages.
• Develop C# scripts within SSIS to support automation and custom processing needs.
• Share insights and updates from BI analysis with stakeholders through regular communication.
• Build strong working relationships with key teams and stakeholders to support business objectives.
• Deliver ad-hoc BI analysis and reports, presenting findings and recommendations to senior management to support strategic decisions and future initiatives.

Skill & Experience

• Eight or more years of professional experience in data engineering.
• Six or more years of experience in roles such as Business Intelligence Engineer, Business Analyst, or Data Engineer within an international or multinational environment.
• At least two years of experience in the retail industry is preferred.