Databricks Expert
Pubblicato il 04-10-2026 - Ntt Data in Treviso
Overview
As a Databricks Expert at NTT DATA, you will bridge Data Science and Data Engineering to craft cloud-native data solutions. You'll support customers on Big Data initiatives, collaborating with analysts and solution architects to align use cases with data needs and outcomes. You'll build and optimize data pipelines, enabling analytics and machine learning through well-governed data lakes. This hybrid role places you in a cross-cultural environment, fostering continuous skill growth and impactful data-driven transformation.
Responsabilità
- Support customers on Big Data projects and collaborate with business analysts and solution architects to understand use cases and outcomes
- Deliver data acquisition, transformations, cleansing, conversion, compression and loading into data lakes for analytics/ML consumption
- Assist in designing data pipelines and enhancements to support analytics and machine learning
- Contribute to PoCs and migration efforts from on-premise to cloud environments
- Monitor and optimize distributed infrastructure using Azure or open-source tooling
Requisiti fondamentali
- Cloud-native experience in at least one of GCP, AWS, or Azure
- 5+ years experience with Databricks (preferred)
- Knowledge of Big Data architectures (cloud and on-premises)
- Azure infrastructure and networking experience
- Experience delivering PoCs addressing business needs with appropriate tech
- Experience migrating workloads from on-prem to cloud
- Experience monitoring distributed infrastructure (Azure tools or Grafana/Prometheus)
- Proven programming skills in Java, Scala, Python, and shell scripting
- SQL proficiency
- Experience leading medium-sized teams
- Hands-on with Spark, Databricks, Azure Data Factory, and Azure Synapse
- Microsoft Certifications relevant to Azure or Databricks
- Leadership and mentoring of teams
- Strong collaboration and cross-functional communication
- Problem-solving mindset with Kaizen approach
- Databricks
- Apache Spark
- Azure D