Senior Data Engineer — Cloud Pipelines & Snowflake

Machine Learning Technologies, LLC; McLean (VA); Hybrid; USD 140,000 - 190,000; Full time

Job summary

Machine Learning Technologies, LLC is seeking a senior data engineer to design, build, and optimize scalable data pipelines on AWS, leveraging Snowflake, PySpark, Glue, and Databricks to support enterprise data products across the organization. You will monitor production workflows, implement observability, respond to incidents via PagerDuty, and collaborate with business and tech teams.

Candidates should have 6+ years in data engineering and be comfortable onsite three days per week in McLean,

Qualifications

• 6+ years of data engineering experience.
• Strong hands-on expertise with AWS data engineering services.
• Proven 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 or Riverwoods, IL.

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

Collaboration

Production support

Observability

Critical data workflows

Tools

AWS

PySpark

AWS Glue

Snowflake

SQL

Databricks

Dashboard development

PagerDuty

Job description

Machine Learning Technologies, LLC is seeking a senior data engineer to design, build, and optimize scalable data pipelines on AWS, leveraging Snowflake, PySpark, Glue, and Databricks to support enterprise data products across the organization. You will monitor production workflows, implement observability, respond to incidents via PagerDuty, and collaborate with business and tech teams.

Candidates should have 6+ years in data engineering and be comfortable onsite three days per week in McLean,