Hybrid Data Engineer - AWS, Snowflake & Pipelines

Artifintech

McLean (VA)

On-site

USD 130,000 - 190,000

Full time

1 hour ago
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Job summary

Artifintech is seeking an experienced Data Engineer to design, build, and optimize scalable data pipelines and cloud-based data solutions on AWS. The role focuses on delivering reliable data products, dashboards, and observability across platforms in a production environment.

The ideal candidate has 6+ years of data engineering experience and hands-on skills with PySpark, AWS Glue, Snowflake, SQL, and Databricks.

Qualifications

  • 6+ years of data engineering experience.
  • Strong hands-on expertise with AWS data engineering services.
  • Experience with PySpark, AWS Glue, Snowflake, SQL, and Databricks.
  • Experience building and supporting enterprise-scale data pipelines.
  • Knowledge of dashboard development, monitoring, and observability solutions.
  • Comfort working in production environments and supporting critical data workflows.
  • Ability to work onsite three days per week in McLean, VA.

Responsibilities

  • Design, develop, and optimize scalable data pipelines.
  • Build data solutions for evolving consumer and business requirements.
  • Develop and maintain cloud-based data engineering solutions on AWS.
  • Use Snowflake for enterprise data storage and processing.
  • Create dashboards and support data consumption across platforms.
  • Implement and enhance monitoring, observability, and operational excellence practices.
  • Monitor production workflows and respond to incidents, including through PagerDuty.
  • Collaborate with business and technology teams to deliver reliable data products.

Skills

Data engineering
Production support

Tools

PySpark
AWS Glue
Snowflake
SQL
Databricks

Job description

Artifintech is seeking an experienced Data Engineer to design, build, and optimize scalable data pipelines and cloud-based data solutions on AWS. The role focuses on delivering reliable data products, dashboards, and observability across platforms in a production environment.

The ideal candidate has 6+ years of data engineering experience and hands-on skills with PySpark, AWS Glue, Snowflake, SQL, and Databricks.

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