Ready The Senior Data Engineer builds, optimizes, and maintains scalable data infrastructure for broadband programs using AWS and GCP. This hands-on role involves designing data models, building Airflow DAGs, and integrating AI/ML workflows.
Responsibilities
Partner with product and engineering teams to translate requirements into technical architecture
Evaluate and recommend data tools, frameworks, and infrastructure
Contribute to roadmap discussions and build-vs-buy decisions
Design, implement, and maintain scalable data infrastructure on AWS
Own data lake and warehouse architecture including partitioning and storage optimization
Build and maintain production-grade Apache Airflow DAGs
Ensure observability across the data platform with monitoring and alerting
Build and maintain robust DBT pipelines with data quality checks
Design and maintain robust database schemas for multi-state, multi-tenant data
Write and optimize SQL queries for analytical and operational workloads
Develop reusable data models, utilities, and shared Python packages
Design data models and infrastructure for large-scale time-series and event-based data
Qualification
Evaluate and recommend data toolsDesignDevelop reusable data models
Required
Partner with product and engineering teams to understand requirements and translate them into the right technical architecture — balancing cost, performance, and long-term maintainability
Evaluate and recommend data tools, frameworks, and infrastructure choices with a pragmatic, product-first mindset
Contribute to roadmap discussions and help the team make informed build-vs-buy decisions
Design, implement, and maintain scalable data infrastructure on AWS (S3, Athena, RDS/PostgreSQL, ECS, Lambda, Secrets Manager, CloudWatch)
Own data lake and warehouse architecture — partitioning strategies, storage optimization, and data lifecycle management
Build and maintain production-grade Apache Airflow DAGs for ingestion, transformation, and export workflows
Ensure observability across the data platform — monitoring, alerting, and fast incident resolution
Build and maintain robust DBT pipelines with data quality checks and well-structured data modeling
Design and maintain robust database schemas to support multi-state, multi-tenant program data
Write and optimize SQL queries across PostgreSQL, Redshift and Athena for analytical and operational workloads
Develop reusable data models, utilities, and shared Python packages that raise the bar for the whole team
Design data models and infrastructure for large-scale time-series and event-based data management at scale
