Data Engineer

Swoon; McLean (VA); Hybrid; USD 83,000 - 152,000; Full time

Job summary

Swoon is seeking a data engineering contractor for hybrid work at McLean, VA or Riverwoods, IL. You will design and implement high-performance data pipelines, ensure data integrity with lineage tracking, and contribute to the data quality framework in a terabyte-scale environment.

Key requirements include expert Python and PySpark, hands-on AWS Glue/EMR, and experience with S3 data lakes and relational databases. Financial services exposure is a plus for this role.

Qualifications

• Expert-level Python and PySpark
• Hands-on AWS Glue and Amazon EMR experience
• Proven track record building scalable data pipelines (Terabyte-scale)
• Experience implementing data lineage and data quality frameworks
• Strong experience with S3-based data lakes and relational databases (RDS/PostgreSQL/MySQL)

Responsibilities

• Designing and implementing high-performance data pipelines that handle large volumes of data
• Ensuring data integrity through advanced quality checks and lineage tracking

Skills

Python

PySpark

Data pipelines

Data quality

Data lineage

Tools

AWS Glue

Amazon EMR

S3

RDS/PostgreSQL/MySQL

Kinesis

Kafka

Job description

Type: Hybrid McLean Virginia OR Riverwoods, Illinois (Chicagoland)

Duration: 11/23/2026 – 6/23/2027

Key Responsibilities:

• Designing and implementing high-performance data pipelines that handle large volumes of data
• Ensuring data integrity through advanced quality checks and lineage tracking

Qualifications:

• Core Languages: Expert-level proficiency in Python and PySpark.
• AWS Ecosystem: Deep hands-on experience with AWS Glue and Amazon EMR.
• Big Data Architecture: Proven track record of building scalable pipelines for large-scale data (Terabyte-scale preferred).
• Data Integrity: Demonstrated experience implementing frameworks for Data Lineage and Data Quality.
• Database Knowledge: Strong experience working with S3-based lakes and relational databases (RDS/PostgreSQL/MySQL).

Preferred Qualifications:

• Industry: Experience within the Financial Services industry is a huge plus.
• Real-time Processing: Experience with Kinesis or Kafka integration for low-latency data delivery.
• DevOps: Familiarity with CI/CD for data pipelines and Infrastructure as Code.