Senior Data Engineer - USD Job Loveland Colorado USA,Software Development

Senior Data Engineer – Remote Contract

Our client is seeking a Senior Data Engineer to join its enterprise data platform team. This team builds and operates a multi-account AWS environment supporting more than a dozen data product teams across the organization. The platform spans data ingestion, transformation, governance and analytics using AWS Glue, Athena, Lake Formation, Redshift, S3 and Apache Iceberg.

This is a fully remote, long-term opportunity for an experienced engineer who can quickly take ownership of production data pipelines and analytics datasets.

What You’ll Do

Design, build and optimize data pipelines using AWS Glue, PySpark and Apache Iceberg
Own data product delivery from source-system ingestion through transformation, quality validation and governed consumption
Build and maintain Amazon Redshift integrations, including schemas, stored procedures, materialized views and Liquibase-managed DDL migrations
Write and optimize complex SQL for analytics transformations, reporting views and data-quality checks
Translate operational data models into star schemas and other dimensional models for analytics
Manage Apache Iceberg tables, including partition and schema evolution, compaction and orphan-file cleanup
Implement table- and column-level governance using Lake Formation permissions, tag-based access control and PII classification
Develop data-quality frameworks covering referential integrity, row-count reconciliation, completeness and anomaly detection
Partner with data product teams to onboard new data sources, define schemas and establish data contracts
Troubleshoot AWS Glue jobs, DMS replication issues and data-freshness problems
Own the complete lifecycle of changes, including development, deployment, validation and communication
Ensure pipelines and datasets remain accurate, reliable and healthy across environments

Required Qualifications

At least five years of hands-on data engineering experience building ETL/ELT pipelines and analytics platforms
Expert-level SQL skills, including complex joins, CTEs, window functions, query optimization and performance tuning
Strong Python and PySpark development experience
Hands-on AWS Glue experience, including job development, bookmarks, crawlers and performance optimization
Strong Amazon Redshift experience, including schema design, stored procedures, Spectrum, external schemas, materialized views and performance tuning
Experience with Apache Iceberg or another open table format, including ACID transactions, schema evolution, partition evolution and table maintenance
Strong understanding of dimensional data modeling, including star schemas, snowflake schemas and slowly changing dimensions
Experience with AWS data services such as Athena, Lake Formation, S3, DMS, Lambda and Event Bridge
Understanding of data governance, tag-based access control, data classification and PII handling
Experience with Liquibase or a similar database migration tool
Familiarity with Git Hub and CI/CD pipelines
Strong attention to data correctness, completeness and freshness
Ability to independently deliver production-ready data pipelines with limited oversight

Preferred Experience

Data Mesh architecture and federated governance
Lakehouse architecture patterns
AWS DMS and change-data-capture ingestion
Terraform or other infrastructure-as-code tools
Data catalog and lineage platforms such as AWS Data Zone or IDERA ER/Studio
AI-assisted development tools such as Amazon Kiro or Git Hub Copilot
Amazon Sage Maker or other machine-learning platforms
Docker and container-based development
Agriculture, retail or other large-scale operational data environments