Senior Data Engineer

Knowledge and Skills Required:

• 7+ years of progressively responsible experience in data engineering with a focus on data modelling and 4+ years in data engineering (Microsoft Fabric or Azure Synapse) and report development (Power BI).
• Proven track record as a Data Engineer or similar role, and in Power BI development, including Paginated or SSRS reports.
• Core Expertise in the Microsoft Data Stack, in particular proficiency with Fabric, Azure Data Factory, Azure Synapse Analytics.
• Proven experience in Data Lake and Data Lakehouse implementation (e.g., Microsoft Fabric, Azure Synapse, Databricks, Snowflake, Microsoft SQL Server, Apache Spark/Hadoop, or other similar big data or SQL databases).
• Experience in Data Vault and dimensional data modeling techniques
• Proficiency in programming languages such as Python, SQL, or Java.
• Proficiency in the Apache Spark framework.
• Knowledge of Finance/Accounting logic in ERP, ideally with D365 F&O. Understanding humanitarian accounting logic is a benefit (appeals, pledges, projects, etc.)
• Experience in data governance, architecture, and handling large datasets and data pipelines.
• Strong knowledge of Azure Cloud architecture and networking principles.
• Familiarity with CI/CD pipelines for data workflows (e.g., using Azure DevOps).
• Proven experience in leadership of a data science (or similar) team, with management of direct reports
• Experience in management and delivery of technical projects
• Proficiency in cloud platforms and technologies, such as AWS, Azure, or Google Cloud.
• Experience with big data technologies, such as Hadoop, Spark, and distributed storage systems.
• Familiarity with data governance, data security, and data privacy regulations (e.g., GDPR, CCPA).
• Familiarity with AI-assisted development
• Experience within the RC/RC Movement and/ or international humanitarian or development organizations.

Responsibilities:

• Analyze and understand business process and data models, business logics, modelling logics, and ways to identify missing data

• Liaise with business contacts or business analysts to understand their needs, and translate these into specifications of requirements

• Identify data requirements and data elements and ingest them in the data platform if missing

• Design and implement complex dashboards and reports in Power BI to provide actionable information

• Follow through on UAT identified issues and their resolution

• Publish data and reports to production

• Maintain dashboards and reports over time Data engineering on Microsoft Fabric/Azure Synapse platform:

• Develop database schemas, define relationships, and optimize performance based on the specific requirements of the data solution

• Develop data products using SQL and PySpark

• Implement data quality checks and processes to ensure data accuracy, consistency, and completeness

• Implement security measures to protect sensitive data and ensure compliance with relevant regulations and standards

• Optimize solutions for performance and scalability

• Identify and resolve performance bottlenecks, optimize SQL queries, and fine-tune data processing workflows

• Document data engineering processes, system architecture, and data flow diagrams for knowledge sharing and future reference Team management:

• Oversee the operation of the full stack developers, managing priorities, interactions, and workload

• Track and document the progress of the team through tools like devops boards

• Propose improvements to processes and technologies, bringing efficiency to the team

• Mentor the development of the team, including the development and refinement of skills