5+ Years Relevant Experience
We are looking for an experienced Senior Data Engineer with deep expertise in PySpark, Python, and SQL, and hands-on experience with the Palantir Foundry platform. This role involves designing and implementing scalable data analytics solutions, transforming complex business requirements into high-quality data models and pipelines, and working in a fast-paced, agile environment.
Key Responsibilities:
- Design, develop, and maintain scalable data pipelines using PySpark, SQL, and Palantir Foundry.
- Translate customer and business requirements into well-architected data analytics solutions.
- Implement data transformation, modeling, and governance practices for enterprise-scale datasets.
- Collaborate with cross-functional teams to integrate data from various sources and ensure data consistency and integrity.
- Optimize and troubleshoot performance across distributed computing environments (e.g., Spark, Hive, Hadoop).
- Contribute to agile delivery practices, including sprint planning, code reviews, and documentation.
Required Skills:
- 5+ years of hands-on experience in PySpark, Python, and SQL (Spark SQL preferred).
- Mandatory: Proven, hands-on experience with the Palantir Foundry platform.
- Strong background in data engineering, data modeling, and building ETL/ELT pipelines.
- Experience with distributed data platforms such as Spark, Hive, or Hadoop.
- Familiarity with cloud environments (Azure or AWS preferred).
- Exposure to Agile/Scrum development methodologies.
- Excellent problem-solving and analytical skills.
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