Data Engineer

At DIGITALL we don't just deliver technology we deliver the future! We are explorers, knowledge-hunters, tech geeks, problem solvers and game changers who want to inspire and be inspired. Our DIGITALL people are always one step forward: working with top-notch technologies, creating innovations ahead of the market trends, sharing the passion for discovering better ways. As a human-centric organization, our teams are built on mutual respect and open communication, allowing everyone to be authentic, express ideas and unleash their potential. We are proud of our DIGITALL bright minds and never stop developing their skills to keep pushing boundaries together and do what we love. DIGITALL operates globally with a team of 1000 experts in 16 locations across 8 countries.

This is your job:

• Design, develop, and maintain scalable enterprise data platforms and pipelines using Microsoft Azure and Microsoft Fabric services.
• Implement and support ETL/ELT processes to ingest, transform, and publish data from multiple internal and external systems.
• Develop Lakehouse-based data solutions using Azure Databricks, Microsoft Fabric, Azure Data Lake Storage (ADLS Gen2), and Apache Spark/PySpark.
• Support the configuration and operation of messaging and event streaming components (e.g., Azure Event Hub, Event Grid, Service Bus) to enable real-time and batch data flows across Azure, Dynamics 365, and SharePoint.
• Support enterprise analytics and reporting initiatives through integration with Power BI semantic models and downstream reporting platforms.
• Participate in the implementation and optimization of CI/CD pipelines and DevOps practices to ensure reliable, repeatable deployments and platform operations.
• Collaborate with cross-functional stakeholders (business, analytics, product, and compliance teams) to understand requirements and translate them into technical solutions.
• Ensure that platform implementations adhere to security, compliance, and operational standards and guidelines.
• Prepare technical documentation, operational runbooks, and knowledge-sharing materials for platform components and services.

Integration / Development Skills (30%)

• Strong hands-on experience with SQL, ETL/ELT design, data transformation, and orchestration frameworks.
• Experience with distributed data processing technologies such as Apache Spark and PySpark.
• Develop and maintain application components and APIs using .NET Core, ASP.NET, C#, Web APIs, and microservices architectures, including APIs that expose or consume data from Dynamics 365 and SharePoint.
• Familiarity with Microsoft Dynamics 365 (CRM), Power Automate, SharePoint is an advantage

Your qualifications:

• Bachelor's degree in Computer Science, Information Systems, Engineering, Data Science, or a related field.
• Minimum 7+ years of experience in data engineering, cloud data platforms, or enterprise analytics solutions.
• Strong hands-on experience with Microsoft Azure data and analytics services, including Azure Databricks, Azure Data Factory, Azure Data Lake Storage (ADLS Gen2), Azure SQL, and Azure Functions.
• Strong experience designing and implementing ETL/ELT pipelines and enterprise data integration solutions.
• Strong command of both relational (SQL Server, PostgreSQL) and NoSQL database systems is expected
• Understanding of Lakehouse and Medallion architecture principles for enterprise analytics platforms.
• Hands-on experience with Apache Spark and PySpark for distributed data processing and transformation.
• Advanced skills in Python are required, including use of data manipulation libraries (Pandas, NumPy) and API integration
• The candidate should demonstrate experience in designing dimensional data models (star/snowflake schemas)
• Ability to design and consume RESTful APIs to integrate data from upstream systems
• Knowledge of visualization tools such as Power BI or Tableau is expected to collaborate effectively with dashboard developers and translate business requirements into well-structured data models that support visualization layers.
• Knowledge of how to structure and prepare data for ML model consumption, including feature engineering, data labeling pipelines, and integration with AI services (e.g., Azure OpenAI, Azure ML)
• Experience working in large enterprise or regulated environments with strong security and compliance requirements is preferred.

Recommended Certifications

• Microsoft Certified: Azure Data Engineer Associate
• Microsoft Certified: Fabric Analytics Engineer Associate
• Microsoft Certified: Azure Solutions Architect Expert
• Microsoft Certified: Azure Developer Associate
• Databricks Certified Data Engineer Associate or Professional

Organizational information:

• All applications will be treated in strict confidentiality
• Please note that only shortlisted candidates will be invited to an interview