Key Responsibilities
−Build and maintain data pipelines on Databricks using Spark and Delta Lake.
−Integrate semiconductor manufacturing data sources (MES, equipment logs, yield data) into the Lakehouse environment.
−Develop efficient ETL/ELT processes to ensure data quality, consistency, and scalability.
−Collaborate with manufacturing engineers and data scientists to deliver clean, reliable datasets for analytics and modeling.
−Document workflows and processes to ensure reproducibility and transparency.
Required Skills −Hands-on experience with Databricks (Spark, Delta Lake, Notebooks).
−Strong proficiency in Python (PySpark) and SQL for data processing and transformation.
−Experience with large-scale data processing (batch and streaming).
−Familiarity with cloud platforms (AWS) and their core data services.
−Requires a minimum of 5 years of related experience with a Bachelor’s degree; or 3 years and a Master’s degree.
Preferred Qualifications −Background in semiconductor manufacturing or IoT data processing.
−Experience with streaming technologies (Kafka, IoT pipelines).
−Exposure to CI/CD tools (GitHub Actions, Jenkins) and orchestration frameworks (Airflow, Prefect).
−Knowledge of Infrastructure-as-Code (Terraform, CloudFormation) is a plus.
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