FREE ACCESS
5,000–10,000 jobs/day
See all jobs on Scoutfield
Search thousands of fresh jobs every day.
Discover
- Fresh listings
- Fast filters
- No subscription required
Create a free account and start exploring right away.
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in building and optimizing data pipelines and Lakehouse solutions using Azure Databricks, while applying best practices in security, governance, and data quality. Proficient in developing AI-powered applications and automating cloud environments with Terraform and CI/CD methodologies.
Highest-signal resume keywords
Azure DatabricksPythonETL/ELTTerraformCloud Security
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Data EngineeringData ModelingSQLPySparkSparkDelta LakeLakehouse ArchitecturesCI/CDInfrastructure as CodeMLOps
Soft Skills
CollaborationCommunication
Tools & Technologies
AzureTerraformMLflowDatabricks GenieAzure Kubernetes Service (AKS)
Certifications & Qualifications
Azure CertificationDatabricks CertificationHashiCorp Certification
Industry Keywords
Cloud EngineeringData ArchitectureGenerative AIGoverned Self-Service AnalyticsData Mesh
Tech Stack
Tools & technologiesAzureCloudETLKubernetesPySparkPythonSparkSQLTerraform
About the role
Key responsibilities & impact- Build and optimize data pipelines and Lakehouse solutions in Azure Databricks
- Develop data models, integrations and analytics capabilities
- Work with modern data architectures, including Lakehouse, Data Mesh and governed self-service analytics
- Create AI-powered applications and Generative AI solutions
- Automate cloud environments using Terraform and CI/CD pipelines
- Apply security, governance and data quality best practices
- Optimize solutions for performance, scalability and cost efficiency
- Collaborate with business and technical stakeholders to deliver reliable, production-ready solutions
Requirements
What you’ll need- 3-6 years of experience in cloud, data engineering or platform engineering
- Hands-on experience with Azure, Azure Databricks and cloud-native services
- Strong knowledge of Python, PySpark and SQL
- Experience with ETL/ELT, Spark, Delta Lake and Lakehouse architectures
- Understanding of Infrastructure as Code, CI/CD and cloud security principles
- Interest in AI and Generative AI technologies
- Fluent English
- Experience with Terraform, MLflow or Databricks Genie
- Knowledge of Azure Kubernetes Service (AKS)
- Exposure to MLOps practices
- Azure, Databricks or HashiCorp certifications
Benefits
Comp & perks- Access to the latest Azure, Databricks and Generative AI technologies
- Learning platforms, technical communities and certification programs
- Flexible working model
- Home office
- International collaboration
- Clear opportunities to grow technical expertise and career within global Data & AI projects