Description
You will design, implement, and optimize scalable data engineering solutions and pipelines within a SaaS environment.
Responsibilities
- Build and maintain data pipeline architecture to move workloads from development to production.
- Assemble large, complex datasets that meet functional and non-functional business requirements.
- Drive optimization, testing, and tooling to improve the quality and velocity of data solutions.
- Manage end-to-end delivery by investigating problem areas and working cross-functionally with product managers and stakeholders.
- Ensure operational effectiveness regarding performance, uptime, and release management of the enterprise data platform.
Required Skills
- 7-15 years of relevant experience in data engineering.
- Strong hands-on experience with Databricks and Unity Catalog.
- Expertise in Python programming and PySpark.
- Proficiency with Apache Spark and the Azure Cloud platform.
- Advanced SQL knowledge and database engineering principles.
- Experience orchestrating workloads on the cloud.
- Ability to handle large, complex datasets from various sources and databases.
- Bachelor's or Master's degree in Computer Science or equivalent experience.
Preferred Skills
- Experience building and leading highly complex technical engineering teams.
- Familiarity with CI/CD methods, APIs, containerization, and orchestration.
- Experience with Teradata.