Data Engineer - PySpark, Snowflake & AWS

McLean, VA, US • Posted 8 hours ago • Updated 8 hours ago
Full Time
On-site
Fitment

Dice Job Match Score™

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Job Details

Skills

  • Streaming
  • Data Deduplication
  • Performance Tuning
  • Caching
  • Optimization
  • Performance Monitoring
  • Data Quality
  • Documentation
  • Collaboration
  • PySpark
  • Cloud Computing
  • Python
  • SQL
  • Amazon S3
  • Electronic Health Record (EHR)
  • Amazon Redshift
  • Snow Flake Schema
  • Extract
  • Transform
  • Load
  • ELT
  • Data Modeling
  • Data Warehouse
  • Orchestration
  • Amazon Web Services
  • Step-Functions
  • Communication

Summary

Our client is seeking an experienced Data Engineer with 8-10 years of expertise to design and build scalable data pipelines using PySpark, Snowflake, and AWS. You will modernize legacy ETL workloads into cloud-native solutions while optimizing performance and ensuring data quality across the platform.

Responsibilities & Qualifications
  • Design and build scalable, production-grade data pipelines using PySpark for batch and streaming processing, including data transformations, deduplication, and performance optimization (partitioning, caching, shuffle optimization)
  • Develop cloud-native data solutions on AWS, leveraging S3, Glue, EMR, Lambda, Step Functions, and Redshift
  • Engineer comprehensive Snowflake data platforms including warehouses, schemas, data models, Iceberg Tables, Dynamic Tables, and Materialized Views
  • Modernize legacy ETL workloads to cloud-based ELT/ETL patterns and implement orchestration using Airflow or AWS Step Functions
  • Optimize Snowflake and PySpark workloads through tuning strategies and performance monitoring to ensure efficiency at scale
  • Ensure data quality, governance, and documentation across all data pipelines, including technical designs and runbooks
  • Collaborate with data architects, analysts, and stakeholders to align solutions with business requirements

Requirements
  • 8-10 years of experience as a Data Engineer with proven expertise in PySpark, Snowflake, and AWS cloud services
  • Advanced proficiency in Python and SQL with the ability to write optimized, production-grade code
  • Strong experience with AWS services including S3, Glue, EMR, Lambda, Step Functions, and Redshift
  • Demonstrated expertise in Snowflake including Iceberg Tables, Dynamic Tables, and Materialized Views
  • Solid understanding of data pipeline design, ETL/ELT patterns, data modeling, and data warehousing best practices
  • Experience with orchestration tools such as Airflow or AWS Step Functions
  • Strong communication skills and ability to work collaboratively with cross-functional technical and business teams
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
  • Dice Id: 91166607
  • Position Id: 90454fef1d32d80c15d1dfaa44058b8e
  • Posted 8 hours ago
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