Sr. Data Engineer

Atlanta, GA - USA

Yearly Salary: $ 140000 - 170000

Posted on: 2 hours ago

Vacancies: 1 Vacancy

Job Summary

We are seeking a Senior Data Engineer (REMOTE) for a full time and direct hire role for one of our amazing partners on the East Coast. You can live in ET or CT time zones but you will need to be available within their core working hours Mon-Fri from 9:00am-12:00pm ET.

This Sr. Data Engineer will be key in developing and managing the data infrastructure enhance the data engineering processes and help optimize and scale their data systems. Our client is a technology company that focuses on customer acquisition within the insurance market and they create personalized experiences for both their clients and customers. They develop scalable products that enhance the shopping journey for consumers and drive customer growth for their clients.

Responsibilities:

Work and collaborate closely with BI Product Engineering and cross-functional stakeholders to gather requirements define data models and deliver actionable data products.
Architect and manage OLAP data platform (Redshift and related components) and partner closely with Product Engineers on OLTP data DevOps to ensure smooth cross-system integrations and data flows.
Design build and maintain scalable ETL/ELT pipelines across batch and real-time environments.
Build and optimize reliable observable and maintainable pipelines using AWS Glue Kafka/Kinesis and Python.
Own and evolve data models that support analytics product usage tracking and real-time decision-making.
Develop and enforce best practices for automated testing data validation quality checks and CI/CD workflows for data systems.
Improve data reliability governance lineage and observability across the stack.
Mentor other engineers and help set strong engineering and data platform standards.

Requirements:

5 years of experience working as a Data Engineer and working with large-scale data systems.
Expert skills using Python for building and orchestrating data pipelines.
Strong experience with AWS Redshift including performance tuning modeling and workload management.
Hands-on experience with AWS Glue Kafka/Kinesis and streaming data patterns.
Proven experience with automated testing frameworks and CI/CD for data.
Strong collaboration skills with both BI teams and Product/Feature teams translating data needs into system designs.
Experience with Data DevOps practices including:
- Managing OLAP data infrastructure
- Coordinating OLTP data integration and operational workflows with product engineering.
- Using tools like Terraform CloudFormation GitHub Actions and CodePipeline.
Experience with ClickHouse or other OLAP/analytical databases is a nice to have.
Exposure to workflow orchestrators (Airflow etc.) is a nice to have.
Experience with Docker ECS EKS or similar container platforms is a nice to have.
Familiar with data observability tooling is a bonus.
Experience with LLMs and MCPs is a nice to have.

All qualified applicants will receive consideration for employment without regard to race color national origin age ancestry religion sex sexual orientation gender identity gender expression marital status disability medical condition genetic information pregnancy or military or veteran status. You must be legally authorized to work in the United States without current or future sponsorship.

We are seeking a Senior Data Engineer (REMOTE) for a full time and direct hire role for one of our amazing partners on the East Coast. You can live in ET or CT time zones but you will need to be available within their core working hours Mon-Fri from 9:00am-12:00pm ET. This Sr. Data Engineer will be...

Responsibilities:

Work and collaborate closely with BI Product Engineering and cross-functional stakeholders to gather requirements define data models and deliver actionable data products.
Architect and manage OLAP data platform (Redshift and related components) and partner closely with Product Engineers on OLTP data DevOps to ensure smooth cross-system integrations and data flows.
Design build and maintain scalable ETL/ELT pipelines across batch and real-time environments.
Build and optimize reliable observable and maintainable pipelines using AWS Glue Kafka/Kinesis and Python.
Own and evolve data models that support analytics product usage tracking and real-time decision-making.
Develop and enforce best practices for automated testing data validation quality checks and CI/CD workflows for data systems.
Improve data reliability governance lineage and observability across the stack.
Mentor other engineers and help set strong engineering and data platform standards.

Requirements:

5 years of experience working as a Data Engineer and working with large-scale data systems.
Expert skills using Python for building and orchestrating data pipelines.
Strong experience with AWS Redshift including performance tuning modeling and workload management.
Hands-on experience with AWS Glue Kafka/Kinesis and streaming data patterns.
Proven experience with automated testing frameworks and CI/CD for data.
Strong collaboration skills with both BI teams and Product/Feature teams translating data needs into system designs.
Experience with Data DevOps practices including:
- Managing OLAP data infrastructure
- Coordinating OLTP data integration and operational workflows with product engineering.
- Using tools like Terraform CloudFormation GitHub Actions and CodePipeline.
Experience with ClickHouse or other OLAP/analytical databases is a nice to have.
Exposure to workflow orchestrators (Airflow etc.) is a nice to have.
Experience with Docker ECS EKS or similar container platforms is a nice to have.
Familiar with data observability tooling is a bonus.
Experience with LLMs and MCPs is a nice to have.