Job Description:
DXC Technology (NYSE: DXC) is a leading enterprise technology and innovation partner delivering software, services, and solutions to global enterprises and public sector organizations — helping them harness AI to drive outcomes at a time of exponential change with speed. With deep expertise in Managed Infrastructure Services, Application Modernization, and Industry-Specific Software Solutions, DXC modernizes, secures, and operates some of the world’s most complex technology estates. Learn more on dxc.com
We are seeking a hands-on Data Engineer experienced in building and supporting modern cloud-based data platforms. This role focuses on designing, developing, and operating scalable data pipelines and transformation workloads using technologies such as Azure Data Factory, Databricks, Microsoft Fabric, and Snowflake.
The successful candidate will contribute to delivering reliable, governed, and high-performing data solutions that support analytics, reporting, and AI initiatives. This role suits an engineer comfortable working across ingestion, transformation, and modelling layers in a collaborative, delivery-focused environment.
Key Responsibilities
Data Pipeline Development
- Design, build, and maintain data ingestion and transformation pipelines using Azure Data Factory and Microsoft Fabric
- Develop batch and near real-time data workflows across structured and semi-structured sources
- Implement orchestration, scheduling, and dependency management
- Monitor pipeline execution and troubleshoot failures
Databricks Engineering
- Develop scalable data transformation solutions using Databricks (PySpark / Spark SQL)
- Build and maintain notebooks, jobs, and reusable frameworks
- Optimise cluster utilisation, job performance, and cost efficiency
- Support Delta Lake design and implementation
Modern Data Platform Delivery
- Contribute to architecture and implementation of lakehouse or warehouse platforms
- Support data modelling and data preparation for downstream analytics
- Implement data quality, validation, and lineage practices
- Participate in platform enhancements and technical improvements
Collaboration & Integration
- Work with architects, analysts, and stakeholders to translate requirements into technical solutions
- Support integration across enterprise systems and cloud services
- Participate in code reviews and collaborative development practices
- Document pipelines, processes, and operational procedures
Operations & Continuous Improvement
- Monitor performance and reliability of data workflows
- Troubleshoot incidents and perform root cause analysis
- Implement logging, alerting, and observability practices
- Identify automation opportunities to improve platform efficiency
Mandatory Skills & Experience
Applicants must demonstrate:
- Proven hands-on experience building data pipelines in modern cloud environments
- Strong experience with Azure Data Factory or Fabric Data Pipelines
- Experience developing transformations in Databricks using PySpark or Spark SQL
- Experience working with Snowflake for data warehousing, transformation, or data sharing workloads
- Solid SQL skills and understanding of data transformation techniques
- Experience working with structured and semi-structured datasets
- Understanding of data engineering lifecycle practices and delivery processes
Technical Platform Experience:
- Microsoft Fabric ecosystem exposure (Lakehouse, Warehouse, or Pipelines)
- Azure data platform components
- Snowflake platform experience including schema design, performance optimisation, and workload management
- Git-based source control practices
Desirable / Nice-to-Have Skills
- Experience designing lakehouse architectures
- Exposure to streaming or event-driven data ingestion technologies (Kafka, Event Hubs, Kinesis)
- Experience with modern transformation and modelling frameworks (dbt or similar)
- Exposure to containerisation or orchestration technologies (Docker, Kubernetes)
- Data modelling for analytics or reporting workloads
- Experience with Power BI or analytics integration
- Infrastructure-as-code or deployment automation (Terraform, Bicep, ARM)
- Knowledge of data governance and cataloguing platforms (Purview, Collibra, Alation)
- Exposure to AI/ML data preparation workflows
- Familiarity with observability or data reliability tooling (Monte Carlo, Great Expectations, or similar)
What We’re Looking For
- A delivery-focused engineer comfortable building solutions hands-on
- Strong problem-solving and troubleshooting skills
- Ability to collaborate across technical and business teams
- Clear communicator with good documentation practices
- Curiosity to learn evolving data platform technologies
Key Outcomes
- Reliable and scalable data pipelines
- Well-performing Databricks workloads
- Trusted, high-quality datasets for analytics and reporting
- Continuous improvement of platform reliability and maintainability
At DXC Technology, we believe strong connections and community are key to our success. Our work model prioritizes in-person collaboration while offering flexibility to support wellbeing, productivity, individual work styles, and life circumstances. We’re committed to fostering an inclusive environment where everyone can thrive.
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