Data Engineer in Albuquerque , New Mexico - #73033 | VanderHouwen

• Albuquerque , New Mexico
• Job Id: 73033
• Data Engineer
• This role is fully remote.
• Data Engineer Responsibilities
• Lead the architecture, development, and maintenance of scalable batch and real-time data pipelines supporting analytics, machine learning, and AI applications.
• Build robust ETL/ELT workflows with data quality, lineage, monitoring, observability, performance, and scalability incorporated throughout the data lifecycle.
• Design data foundations for LLM and generative AI solutions, including unstructured data ingestion, preprocessing, enrichment, embedding pipelines, vector stores, retrieval optimization, and RAG workflows.
• Architect cloud-based data solutions within AWS using technologies such as S3, Glue, Redshift, Athena, EMR, Kinesis, MSK, Lambda, Step Functions, EventBridge, Lake Formation, and IAM.
• Establish data contracts, engineering standards, and reusable architecture patterns while ensuring consistency across assigned projects and workstreams.
• Own data engineering delivery from requirements through implementation, including technical planning, estimation, sequencing, dependency management, and proactive identification of delivery risks.
• Partner directly with clients and stakeholders to assess data readiness, gather requirements, identify gaps, and translate operational or product needs into practical data architecture recommendations.
• Collaborate with software engineering, analytics, platform, DevOps, product, and machine learning teams to ensure data solutions effectively support downstream applications and business objectives.
• Develop clear technical documentation, architecture diagrams, integration designs, and other materials that support project delivery, knowledge sharing, and client communication.
• Mentor less experienced engineers through code reviews, architecture discussions, pairing, and technical guidance while contributing to engineering standards and internal best practices.
• Data Engineer Qualifications
• Significant professional experience designing and delivering production-grade data pipelines, platforms, and cloud-based data architectures with the ability to operate independently on complex initiatives.
• Strong hands-on experience with ETL/ELT development, data modeling, batch and streaming architectures, data quality, lineage, monitoring, observability, and performance optimization.
• Advanced experience with AWS data services, ideally including S3, Glue, Redshift, Athena, EMR, Kinesis and/or MSK, Lambda, Step Functions, EventBridge, Lake Formation, and IAM.
• Experience building data infrastructure for AI or LLM applications, including embeddings, vector databases, unstructured data processing, retrieval architectures, and RAG-based solutions.
• Demonstrated ability to make technical architecture decisions, establish standards or data contracts, and take end-to-end ownership of a data engineering workstream.
• Experience with cloud security, governance, infrastructure-as-code, and automated provisioning practices; exposure to FedRAMP or similarly regulated environments is highly valued.
• Strong understanding of data lakes, data warehouses, streaming platforms, and architectures supporting predictive or real-time machine learning workloads.
• Proven ability to translate business and product requirements into scalable, maintainable technical solutions while identifying dependencies and potential risks early.

None flagged.