Skyworks is looking for a Principal Data Engineer to lead the design and implementation of scalable, high-performance data solutions using cloud-native architectures on Azure, Databricks, Kafka, and Spark to shape their data strategy and drive innovation.
Requirements
- Expertise in Azure, Databricks, Apache Spark, Kafka, and Cassandra.
- Strong programming skills in Python, SQL, and Scala.
- Experience with distributed systems, data modeling, and data warehousing.
- Familiarity with machine learning pipelines, MLOps, and cloud-native architectures.
- Exposure to big data tools and distributed computing.
- Certifications in Azure or Databricks are a plus.
Responsibilities
- Architect and implement scalable data pipelines using Apache Spark, Databricks, and Azure Data Factory.
- Lead the development of real-time streaming solutions using Apache Kafka.
- Design and optimize ETL/ELT workflows for structured and unstructured data.
- Build and maintain distributed data systems using Cassandra, Delta Lake, and other modern data stores.
- Utilize Delta Live Tables (DLT) to create reliable, maintainable, and testable batch and streaming pipelines.
- Integrate Databricks with Azure Machine Learning, Azure Synapse, and other cloud services.
- Implement CI/CD pipelines using Azure DevOps, Terraform.
Other
- Bachelor's degree and 12+ years of experience in data engineering, with at least 3 years in a principal or lead role.
- Proven ability to lead cross-functional teams and deliver complex data solutions.
- Excellent communication, problem-solving, and leadership skills.
- Mentor junior engineers and foster a culture of technical excellence and innovation.
- Collaborate with global Agile teams to deliver high-quality solutions.
