Описание

This role is a senior data engineering position focused on building large-scale data pipelines and lakehouse solutions. It requires strong experience with PySpark, Cloudera Data Platform, Apache Iceberg, and Apache Airflow. AWS data services are also part of the expected expertise.

Responsibilities

Building large-scale data pipelines and lakehouse solutions

Requirements

Bachelor's degree in Computer Science, Information Systems, Engineering, or related field
5+ years of IT experience with 5+ years in Data Engineering and Big Data development
Strong hands-on experience with PySpark and Spark-based data processing
Experience developing data pipelines on Cloudera Data Platform (CDP)
Strong knowledge of Apache Iceberg table architecture and data lake concepts
Experience designing and managing workflows using Apache Airflow
Experience with SQL and data modeling techniques
Strong understanding of ETL/ELT development and data transformation frameworks
Experience working with large-scale structured and unstructured datasets
Knowledge of Git, CI/CD pipelines, and DevOps practices
Strong analytical, troubleshooting, and problem-solving skills
Excellent communication and collaboration skills

Nice to have

Experience with AWS services including S3, Glue, Lambda, ECS/EKS, EMR, RDS, IAM, and CloudWatch
Experience building cloud-native data lake and Lakehouse solutions
Strong knowledge of data partitioning, performance tuning, and query optimization
Experience with Kafka or event-driven data processing frameworks
Experience with Java or Python application development
Experience implementing data quality, metadata, and data governance solutions
Healthcare, Medicaid, Claims Processing, or Insurance industry experience
Experience working in Agile development environments
AWS Certification and/or Cloudera Certification preferred
Experience supporting large-scale cloud migration and modernization initiatives

We offer

Diversity, equity and inclusion as core values

Hiring process

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