Senior Data Engineering Consultant
Skills
Azure Data FactoryAzure Data LakeC#DevopsAnalyticsApache SparkBusiness Intelligence
What the job involves
The main requirements, responsibilities and hiring steps.
Requirements
- Good understanding of Microsoft Azure and cloud computing concepts
- Strong hands-on experience with Apache Spark or Databricks
- Proficient in Python for data engineering solutions
- Advanced SQL skills including complex high-performance queries
- Experience with Azure Data Factory or similar orchestration tools
- Knowledge of Azure Data Lake storage and Delta Lake
- Experience with Unity Catalog Purview or similar governance tools
- Experience using Terraform Azure DevOps or other IaC tools
- Ability to gather requirements and consult with clients
- Agile project management experience
- Understanding of object-oriented development practices
- Knowledge of ETL approaches including data quality resilience and observability
- Understanding of CI/CD methodologies and SDLC
Nice to have
- Client focused
- Technically passionate
- Empathetic
- Knowledge sharing
- Agile mindset
- Collaborative
- Inclusive
Day to day
- Design and deliver advanced data engineering solutions on modern cloud platforms, with a strong focus on Azure and Databricks.
- Build reliable, end-to-end data pipelines and data platforms using Python, SQL, Spark and orchestration tools such as Azure Data Factory.
- Work closely with clients and internal teams to gather requirements, lead projects, and translate business needs into pragmatic technical solutions.
- Champion best practices in data quality, resilience, observability, governance and CI/CD while sharing knowledge across the wider data community.
Hiring process
- Get to know you chat with the People Recruitment Manager
- Technical competency with the Hiring Lead and a Team Member