Data Engineer

Unisys; McLean (VA); On-site; USD 130,000 - 170,000; Full time

Job summary

Unisys is seeking a Data Engineer to design, build, and optimize scalable data pipelines using a modern AWS data stack. You will leverage Python, PySpark, AWS Glue, and Amazon EMR to deliver trusted data across enterprise platforms.

Required experience includes data quality and lineage, strong SQL with PostgreSQL/MySQL/AWS RDS, and familiarity with real-time processing tools such as Kafka or AWS Kinesis. IaC tools and Agile practices are a plus.

Qualifications

• 5+ years of Data Engineering experience.
• Expert Python and PySpark skills.
• Hands-on with AWS Glue and Amazon EMR.
• Experience building large-scale terabyte-scale data pipelines.
• Strong knowledge of Amazon S3 Data Lakes.
• Experience with Data Quality and Data Lineage implementations.
• Experience with PostgreSQL, MySQL, or AWS RDS.
• Excellent problem-solving and performance tuning.

Skills

Python

PySpark

AWS Glue

Amazon EMR

Data Quality

Data Lineage

PostgreSQL

MySQL

AWS RDS

Performance Tuning

Problem Solving

Tools

Kafka

AWS Kinesis

Terraform

CloudFormation

CI/CD

Job description

We are seeking a highly skilled Data Engineer to design, develop, and optimize scalable data pipelines that process large volumes of data. The ideal candidate will have deep expertise in Python, PySpark, AWS Glue, and Amazon EMR, along with experience implementing data quality and lineage frameworks to ensure data integrity across enterprise data platforms.

Required Qualifications

• 5+ years of Data Engineering experience.
• Expert-level proficiency in Python and PySpark.
• Strong hands-on experience with AWS Glue and Amazon EMR.
• Experience building and supporting large-scale data pipelines (terabyte-scale preferred).
• Strong knowledge of Amazon S3 Data Lakes.
• Experience with Data Quality and Data Lineage implementations.
• Strong experience with PostgreSQL, MySQL, or AWS RDS.
• Excellent problem-solving and performance-tuning skills.

Preferred Qualifications

• Experience in the Financial Services industry.
• Hands-on experience with Kafka or AWS Kinesis for real-time data processing.
• Knowledge of CI/CD pipelines for data engineering workflows.
• Experience with Infrastructure as Code (IaC) tools such as Terraform or CloudFormation.
• Familiarity with Agile development methodologies.