data engineer

Our client is seeking a highly skilled and experienced Data Engineer to join their data analytics team. In this role, you will be responsible for collecting, processing, and transforming raw data from multiple sources into clean, structured datasets that enable data-driven decision-making. Additionally, you will collaborate with internal stakeholders, manage change requests, work with external vendors, and ensure compliance with internal processes and audits, always applying best practices in data governance, security, and quality management. Your technical expertise will be crucial in building efficient and reliable data pipelines, ensuring high availability, optimal performance, and driving cost optimization.

Responsibilities:

• Work closely with business partners across all levels of the organization to understand their operations, system, and data challenges and opportunities to define and recommend data analytics solutions that enable the organization to achieve its strategic priorities and goals.
• Support our client by designing, building, and maintaining data pipelines that collect, store, analyze, and visualize enterprise data through reports, dashboards, data marts, and other information delivery artifacts.
• Support in developing and implementing an overall organizational data strategy, including data model designs, database development standards, and management of data warehouses, data analytics, and ML systems.
• Remain knowledgeable and consistently apply organizational policies and governance guidelines related to data access and security.
• Execute and contribute to defining and including new internal/ external data sources, optimizing data flows, and integrating new technologies and processes toward a consistent, reliable, and unified data hub.
• Monitor and take appropriate action to maintain the integrity of their DWH (Synapse Analytics), Databricks, and data lake solutions, including data quality and operational issues.
• Conduct complex data analysis and create reports & dashboards to convey key insights
• Be able to analyze, organize, and combine raw data information from different sources.

Competencies:

• Experience collecting requirements and building data analysis solutions to convert raw data into usable information for analysts and business users.
• Technical expertise in data modeling, data mining, and ML model development (i.e., classification, segmentation, prediction, etc.)
• Familiarity with Agile development practices and frameworks
• Team spirit with excellent communication and interpersonal skills
• Strong organization and analytical skills with the ability to manage multiple priorities
• Ability to multitask and work efficiently
• Effective time management and ability to meet deadlines
• Results-oriented approach with keen attention to high quality, details and accuracy
• Excellent use of English language both written and verbal.

Educational Level:

• Bachelor’s Degree in Computer Science, Information Systems, Computer Science, or a related field.
• Master’s degree in Business Data Science, Intelligence, Data Analytics or AI would be an asset

Other Knowledge:

• Knowledge of Programming language and experience in R and/ or Python for analytical problem-solving.
• Experience in predictive modeling, model validation, and model operationalization.
• Experience working with Microsoft Azure, including services like Azure Data Factory (ADF), Azure Logic Apps, Azure Functions, Azure Data Lake Storage (ADLS), MS Power BI, and MS Paginated Report.
• Hands-on experience with Azure Databricks, Synapse Analytics, or other distributed data processing frameworks.
• Exposure to business & operational analytics ingesting data from CRM, Billing, ERP, and other enterprise information systems.
• Data engineering certification (e.g., Azure Data Engineer Associate, Databricks Certified Data Engineer Associate, etc.) will be considered an asset.
• Familiarity with the Energy & Utilities business domain.

Work Experience:

• 3+ years of experience with data management platforms such as MS SQL Server, MS Analysis Services, Azure SQL Database, Azure Data Lake, and Microsoft Dataverse.
• 3+ years of experience with traditional ELT/ ETL and/ or emerging integration platforms, such as BizTalk, SSIS, Azure Data Factory, DataBricks and Azure Logic Apps
• 2+ years of experience with Power BI platform, including Power BI Desktop, Power BI Report Builder, and Power BI Service with Premium Capacity.