The Senior Data Engineer is responsible for leading the implementation and operationalization of the Elections Redshift analytics platform improving reporting performance ensuring reporting accuracy and establishing a scalable analytics foundation for the TEAM system. This role is expected to transform reporting from a known operational bottleneck into a strategic capability by delivering the Redshift implementation validating reporting accuracy and improving Public Information Request (PIR) workflows. The role will work closely with stakeholders Product Engineering QA and AWS to ensure reporting is performant accurate auditable and scalable. Based on the Redshift PoC the objective is to move reporting workloads away from the transactional PostgreSQL database and into a dedicated analytics environment using Redshift and CDC-based replication.
Definition of Success:
Success will be measured through tangible business and operational improvements including:
Faster PIR turnaround times
Faster report execution times
Improved reporting accuracy
Elimination of report reconciliation issues
Reduced load on transactional databases
Improved data quality
Improved stakeholder confidence in reporting
Increased analytics platform adoption
Successful Redshift production readiness
Executive Expectation:
The expectation is to leave reporting analytics and data quality capabilities materially better than they were found within the first 90 days. Success is not measured by activity alone but by delivering a production-ready Redshift analytics platform improving PIR performance and accuracy establishing trusted reporting across the TEAM ecosystem and creating the foundation for a modern analytics experience for Elections.
Required Skills:
5 years of experience as a Data Engineer or in similar data engineering roles. Strong experience designing and implementing enterprise Data Quality frameworks. Hands-on experience with GX Core (Great Expectations) or similar tools such as Soda. Strong SQL skills and experience working with Aurora PostgreSQL and Amazon Redshift. Experience designing data validation rules reconciliation processes and observability solutions. Experience building and maintaining ETL pipelines and large-scale data workflows. Strong understanding of data modeling referential integrity synchronization and batch processing. Experience integrating data validation into CI/CD pipelines. Experience with Git and engineering best practices such as Rule-as-Code. Experience building dashboards alerts and reporting for operational monitoring. Strong analytical and problem-solving skills with experience performing root cause analysis. Experience collaborating with cross-functional engineering teams. Excellent communication and documentation skills.
Required Education:
System Engineer
Este es un puesto de trabajo remoto. Role Objective: The Senior Data Engineer is responsible for leading the implementation and operationalization of the Elections Redshift analytics platform improving reporting performance ensuring reporting accuracy and establishing a scalable analytics foun...
Este es un puesto de trabajo remoto.
Role Objective:
The Senior Data Engineer is responsible for leading the implementation and operationalization of the Elections Redshift analytics platform improving reporting performance ensuring reporting accuracy and establishing a scalable analytics foundation for the TEAM system. This role is expected to transform reporting from a known operational bottleneck into a strategic capability by delivering the Redshift implementation validating reporting accuracy and improving Public Information Request (PIR) workflows. The role will work closely with stakeholders Product Engineering QA and AWS to ensure reporting is performant accurate auditable and scalable. Based on the Redshift PoC the objective is to move reporting workloads away from the transactional PostgreSQL database and into a dedicated analytics environment using Redshift and CDC-based replication.
Definition of Success:
Success will be measured through tangible business and operational improvements including:
Faster PIR turnaround times
Faster report execution times
Improved reporting accuracy
Elimination of report reconciliation issues
Reduced load on transactional databases
Improved data quality
Improved stakeholder confidence in reporting
Increased analytics platform adoption
Successful Redshift production readiness
Executive Expectation:
The expectation is to leave reporting analytics and data quality capabilities materially better than they were found within the first 90 days. Success is not measured by activity alone but by delivering a production-ready Redshift analytics platform improving PIR performance and accuracy establishing trusted reporting across the TEAM ecosystem and creating the foundation for a modern analytics experience for Elections.
Required Skills:
5 years of experience as a Data Engineer or in similar data engineering roles. Strong experience designing and implementing enterprise Data Quality frameworks. Hands-on experience with GX Core (Great Expectations) or similar tools such as Soda. Strong SQL skills and experience working with Aurora PostgreSQL and Amazon Redshift. Experience designing data validation rules reconciliation processes and observability solutions. Experience building and maintaining ETL pipelines and large-scale data workflows. Strong understanding of data modeling referential integrity synchronization and batch processing. Experience integrating data validation into CI/CD pipelines. Experience with Git and engineering best practices such as Rule-as-Code. Experience building dashboards alerts and reporting for operational monitoring. Strong analytical and problem-solving skills with experience performing root cause analysis. Experience collaborating with cross-functional engineering teams. Excellent communication and documentation skills.
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