We are looking for a Data Engineer to support education-focused data initiatives through a Contract engagement based in Carmichael, California. This role will design and enhance reliable data pipelines that turn complex source information into trusted, well-structured datasets for reporting, analysis, and future advanced use cases. The ideal candidate brings strong engineering judgment, clear communication skills, and hands-on experience building scalable solutions in cloud-based environments. Responsibilities: • Build and maintain multi-stage data pipelines that organize raw, refined, and curated data for downstream business and analytics use. • Develop incremental processing workflows that efficiently capture updates and propagate changes across datasets with accuracy and consistency. • Create approaches for matching and unifying records across separate platform instances where identifiers may overlap or conflict. • Establish data lineage, traceability, and audit controls so datasets can be validated and reviewed with confidence. • Implement and manage workflow orchestration for scheduled and event-driven pipeline execution using cloud-native or equivalent automation tools. • Write production-quality pipeline code in Python and TypeScript to support ingestion, transformation, and delivery of data assets. • Leverage AWS services such as Lambda and S3 to build resilient, scalable components for data processing workloads. • Partner with technical and non-technical stakeholders to explain design decisions, clarify tradeoffs, and align solutions with operational needs. • Prepare data models and pipeline outputs that can support future AI and machine learning applications, including training and inference workflows.

• 5+ years of experience in data engineering, ETL development, or closely related data platform work. • Strong command of Python for pipeline development; familiarity with TypeScript in engineering implementations is also expected. • Hands-on experience with modern data architecture patterns, including layered pipeline design and incremental data processing. • Proficiency with AWS-based data solutions, including services such as Lambda and S3, in production environments. • Working knowledge of orchestration frameworks such as Step Functions, Airflow, or comparable workflow management tools. • Experience with big data and streaming technologies such as Apache Spark, Apache Hadoop, and Apache Kafka. • Understanding of data governance practices including lineage, auditability, and reliable change tracking across systems. • Ability to communicate complex technical topics clearly to both technical teams and business stakeholders.

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Carmichael, CA
onsite
Temporary / Contract
60 - 70 USD / Hourly
We are looking for a Data Engineer to support education-focused data initiatives through a Contract engagement based in Carmichael, California. This role will design and enhance reliable data pipelines that turn complex source information into trusted, well-structured datasets for reporting, analysis, and future advanced use cases. The ideal candidate brings strong engineering judgment, clear communication skills, and hands-on experience building scalable solutions in cloud-based environments. Responsibilities: • Build and maintain multi-stage data pipelines that organize raw, refined, and curated data for downstream business and analytics use. • Develop incremental processing workflows that efficiently capture updates and propagate changes across datasets with accuracy and consistency. • Create approaches for matching and unifying records across separate platform instances where identifiers may overlap or conflict. • Establish data lineage, traceability, and audit controls so datasets can be validated and reviewed with confidence. • Implement and manage workflow orchestration for scheduled and event-driven pipeline execution using cloud-native or equivalent automation tools. • Write production-quality pipeline code in Python and TypeScript to support ingestion, transformation, and delivery of data assets. • Leverage AWS services such as Lambda and S3 to build resilient, scalable components for data processing workloads. • Partner with technical and non-technical stakeholders to explain design decisions, clarify tradeoffs, and align solutions with operational needs. • Prepare data models and pipeline outputs that can support future AI and machine learning applications, including training and inference workflows.
2026-06-29T00:00:00Z

Data Engineer Job in Carmichael, CA | Robert Half