Data Engineering Solutions Manager

We are seeking an experienced data engineer to join our product development team. As a seasoned professional, you will be responsible for designing, building, and optimizing data pipelines and architectures.

Your primary focus will be on mentoring junior engineers, collaborating across teams, and delivering scalable data solutions.

You will work closely with data scientists, analysts, and business stakeholders to understand data needs and deliver robust solutions.

The ideal candidate will have 8 years of experience in data engineering, including a minimum of two years on Azure.

Proficiency in SQL, Python, and Spark is required, along with experience with Azure cloud services such as Data Factory, Synapse, Blob Storage, Functions, ADLS gen2, and Data Bricks.

Azure Services: Experience with Azure cloud services such as Data Factory, Synapse, Blob Storage, Functions, ADLS gen2, and Data Bricks.

Microsoft Fabric: Advanced expertise in Microsoft Fabric.

Data Management: Familiarity with data governance, lineage, and cataloging tools.

Data Warehousing: Strong understanding of data warehousing concepts and dimensional modeling.

Methodologies: Proficient with version control (Git), CI/CD, and Agile methodologies.

Communication: Excellent communication and collaboration skills.

Certification: Microsoft Azure Data Engineer certification is an advantage.

• Design and implement scalable data pipelines using Azure Data Factory, Synapse Pipelines, and Apache Spark on Azure Fabric.
• Architect and maintain data models and storage solutions using OneLake, Delta Lake, Parquet, ADLS gen2.
• Develop and optimize Dataflows Gen2, Notebooks, and KQL queries for data transformation and exploration.
• Collaborate with data scientists, analysts, and business stakeholders to understand data needs and deliver robust solutions.
• Implement data governance, lineage, and quality frameworks using Microsoft Purview and Fabric Data Activator.
• Support CI/CD pipelines and automation for data workflows using Azure DevOps or GitHub Actions.
• Integrate external datasets by working with APIs and third-party data sources.
• Ensure security, compliance, and performance of data systems.
• Mentor junior engineers and contribute to best practices and architectural standards.

• Education: A bachelor's degree or higher in Computer Science, Information Systems, or a related field.
• Experience: 8 years of experience in data engineering, including a minimum of two years on Azure.
• Proficiency: Skilled in SQL, Python, and Spark.
• Azure Services: Experience with Azure cloud services such as Data Factory, Synapse, Blob Storage, Functions, ADLS gen2, and Data Bricks.
• Microsoft Fabric: Advanced expertise in Microsoft Fabric.
• Data Management: Familiarity with data governance, lineage, and cataloging tools.
• Data Warehousing: Strong understanding of data warehousing concepts and dimensional modeling.
• Methodologies: Proficient with version control (Git), CI/CD, and Agile methodologies.
• Communication: Excellent communication and collaboration skills.
• Certification: Microsoft Azure Data Engineer certification is an advantage.

• Cloud Platform: Advanced expertise in Microsoft Azure, with a particular focus on Microsoft Fabric.
• Data Engineering: Proficiency in Azure Data Factory, Azure Synapse Analytics, and Apache Spark.
• Lakehouse Architecture: Familiarity with OneLake, Delta Lake, Parquet, Delta, Iceberg, and Hudi.
• Warehousing: Proficiency in star/snowflake schemas, dimensional modeling, and satellite hub models.
• Programming: Expertise in Python, PySpark, SQL, and KQL (Kusto Query Language).
• Data Orchestration: Firsthand experience with Dataflows Gen2 and Notebooks.
• DevOps & CI/CD: Proficiency in Azure DevOps, Git, and YAML pipelines.
• Security & Governance: Advanced understanding of Microsoft Purview, RBAC, and data masking techniques.