Data Engineer Palantir

EXL SERVICE
United States
3 months ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Experienced
Experience required
3 years minimum
Working hours
Regular working hours
Job source

Tech stack

JavaScript (Programming Language) Artificial Intelligence Amazon S3 Big Data Cloud Computing Information Engineering Extract Transform Load (ETL) Distributed Systems Python (Programming Language) Performance Tuning Tensorflow TypeScript
+9 more
Data Processing Pytorch Snowflake Pyspark Kubernetes Machine Learning Operations Data Pipelines Docker Microservices

Requirements

Job Description: · 3+ years of hands-on experience in data engineering with a focus on ETL workflows, data pipelines, and cloud computing.

· Strong experience with AWS services for data processing and storage (e.g., S3, Glue, Athena, Lambda, Redshift).

· Proficiency in programming languages such as Python, PySpark, and TypeScript/JavaScript.

· Deep understanding of microservices architecture and distributed systems.

· Familiarity with AI/ML tools and frameworks (e.g., TensorFlow, PyTorch) and their integration into data pipelines.

· Experience with big data technologies like Snowflake.

· Strong problem-solving and performance optimization skills.

· Exposure to modern DevOps practices, including CI/CD pipelines and container orchestration tools like Docker and Kubernetes.

· Experience working in agile environments delivering complex data engineering solutions.

· Proven expertise or certification in Palantir Foundry is highly preferred.

· Prior experience in the insurance domain is highly desirable.

Responsibilities: · 3+ years of hands-on experience in data engineering with a focus on ETL workflows, data pipelines, and cloud computing.

· Strong experience with AWS services for data processing and storage (e.g., S3, Glue, Athena, Lambda, Redshift).

· Proficiency in programming languages such as Python, PySpark, and TypeScript/JavaScript.

· Deep understanding of microservices architecture and distributed systems.

· Familiarity with AI/ML tools and frameworks (e.g., TensorFlow, PyTorch) and their integration into data pipelines.

· Experience with big data technologies like Snowflake.

· Strong problem-solving and performance optimization skills.

· Exposure to modern DevOps practices, including CI/CD pipelines and container orchestration tools like Docker and Kubernetes.

· Experience working in agile environments delivering complex data engineering solutions.

· Proven expertise or certification in Palantir Foundry is highly preferred.

· Prior experience in the insurance domain is highly desirable.

Qualifications: · 3+ years of hands-on experience in data engineering with a focus on ETL workflows, data pipelines, and cloud computing.

· Strong experience with AWS services for data processing and storage (e.g., S3, Glue, Athena, Lambda, Redshift).

· Proficiency in programming languages such as Python, PySpark, and TypeScript/JavaScript.

· Deep understanding of microservices architecture and distributed systems.

· Familiarity with AI/ML tools and frameworks (e.g., TensorFlow, PyTorch) and their integration into data pipelines.

· Experience with big data technologies like Snowflake.

· Strong problem-solving and performance optimization skills.

· Exposure to modern DevOps practices, including CI/CD pipelines and container orchestration tools like Docker and Kubernetes.

· Experience working in agile environments delivering complex data engineering solutions.

· Proven expertise or certification in Palantir Foundry is highly preferred.

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