Data Engineer - Databricks & Cloud Data Platform
Indexed description
Why ERNI is the Perfect Place for You: 🏡
- International Exposure: Work with global clients on cutting-edge projects.
- Inclusive Culture: Thrive in a collaborative and diverse work environment.
- Career Development: Enjoy continuous learning and professional growth opportunities.
- Challenging Projects: Engage in complex software projects across MedTech, Industry, Finance, and Transportation.
- Supportive Environment: Benefit from a team dedicated to guiding and supporting your success.
- Recognition and Advancement: Receive acknowledgment for your efforts and opportunities for promotion.
- Open Communication: Experience transparency and value your input in our culture.
- Hands-on experience supporting or administering Databricks environments in production.
- Experience supporting enterprise data pipelines and ETL/ELT processes.
- Strong knowledge of Apache Spark, PySpark, and SQL.
- Experience working with AWS and/or Azure cloud services.
- Good understanding of data engineering principles and distributed processing architectures.
- Python programming skills for automation, troubleshooting, and operational support.
- Strong analytical and problem-solving capabilities.
- Experience troubleshooting complex technical and operational issues.
- Excellent verbal and written English communication skills.
- Ability to create and maintain clear technical documentation and operational procedures.
- Databricks certifications.
- Experience with Airflow, Azure Data Factory, AWS Glue, or other workflow orchestration tools.
- Experience with Git, Jenkins, CI/CD pipelines, containers, and DevOps practices.
- Familiarity with ITIL-based service management environments.
- Experience with ServiceNow or similar IT Service Management (ITSM) platforms.
- Exposure to enterprise-scale cloud data platform operations.
- Provide operational support for Databricks-based enterprise data platforms.
- Investigate and resolve incidents affecting data pipelines, workflows, clusters, integrations, and platform services.
- Troubleshoot Spark, PySpark, Spark SQL, and ETL/ELT workloads running in production environments.
- Monitor platform health and identify potential risks before they impact users and business processes.
- Support incident management, root cause analysis, and problem management activities.
- Collaborate with engineering, platform, and product teams to resolve complex technical issues.
- Support data services deployed on AWS and/or Azure cloud platforms.
- Create and maintain technical documentation, operational runbooks, and knowledge base articles.
- Contribute to automation initiatives and service improvement opportunities.
- Help improve operational efficiency, service reliability, and platform scalability.
Type: Project-based (minimum 1 year, subject to extension) / Staff Augmentation
Switzerland
- Germany
- Spain
- Slovakia
- Romania
- Philippines
- Singapore
- USA
+63 5310 1707 | www.betterask.erni | [email protected]
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