• Lead the architecture and development of scalable, secure data pipelines supporting AI/ML workloads • Own end to end data engineering processes: ingestion, transformation, storage, quality, and monitoring • Collaborate with data scientists and ML engineers on model features, training pipelines, and deployment • Drive best practices in data modeling, orchestration, versioning, and performance optimization • Mentor and guide junior engineers • Ensure data governance, lineage, and compliance standards are met across platforms • Support real time and batch processing frameworks in production environments

• Lead Financial data modeling and data product delivery • Oversee the design and buildout of ETL/ELT data pipelines • Implement best practices for performance tuning and data governance • Create documentation for data pipelines, workflows, and processes • Share best practices and mentor junior data engineers

Role Description Join a team of bright, motivated professionals using agile methodologies to design, build, and transform business solutions through a major ERP modernization initiative at Los Alamos National Laboratory. As part of the Business Applications and Data Services (ADS-BADS) organization, you will play a key role in executing an enterprise-wide data strategy to modernize LANL's core operational data environment and transition to a scalable, cloud-native platform. - Define enterprise data strategy, standards, and architectural blueprints - Lead modernization of legacy data environments to cloud-native platforms - Design and implement large-scale data architectures and data warehouses - Plan and execute complex data migrations including on-premises to cloud and cloud to cloud - Partner with ERP planners, integrators, and institutional subject matter experts - Ensure data integrity, security, governance, and accessibility across the enterprise - Provide technical leadership and direction across multiple concurrent initiatives - Present architectural strategies and decisions to executive stakeholders - Collaborate cross-functionally with business analysts, developers, infrastructure, and ERP teams Qualifications - 15+ years of progressive experience in data architecture and modernization - Extensive experience with one or more of: Snowflake, Databricks, or SAP data platforms (S/4HANA, Datasphere, etc.) - Proven experience as a Senior Data Architect on large-scale programs - Strong background in data warehousing, enterprise data platforms, and large-scale modernization initiatives - Deep understanding of major cloud platforms and native data services - Significant data migration experience - Demonstrated ability to lead technical teams - Strong stakeholder engagement and executive presentation skills - Excellent written and verbal communication skills - Bachelor's degree and 12+ years of related experience, or equivalent combination of education and experience Requirements - Must be a U.S. Citizen - required for Q Clearance eligibility, no exceptions - Must have 15+ years of progressive experience in data architecture and modernization - Must have hands-on experience with Snowflake, Databricks, or SAP data platforms - Must have proven Senior Data Architect experience on large-scale enterprise programs - Must be able to obtain a DOE Q Clearance - subject to federal background investigation Desired Qualifications - Master's degree in Computer Science, Information Systems, or a related field - Experience with SAP Business Data Cloud (BDC), SAP Business Technology Platform (BTP), or SAP Integration Suite - Experience leading architecture for data lakes, lakehouses, ETL/ELT pipelines, and streaming architectures - Experience implementing enterprise data catalogs and governance programs - Familiarity with big data technologies and machine learning concepts - ERP certifications such as SAP, Oracle, or Workday

Role Description Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark, General Catalyst, Peter Thiel, Adam D'Angelo, Larry Summers, and Jack Dorsey. Position: Data Engineer (Coding Agent Experience) Type: Contract Compensation: $80/hour Location: Remote Role Responsibilities - Use frontier AI coding agents to complete and evaluate complex data engineering tasks. - Review model-generated implementations involving ETL pipelines, data warehouses, analytics platforms, and distributed data systems. - Identify bugs, edge cases, scalability issues, and failure modes in model outputs. - Compare outputs from multiple frontier models and assess their strengths and weaknesses. - Apply professional engineering judgment to realistic data engineering scenarios. Qualifications - Must-Have: 2+ years of professional data engineering experience. - Experience building ETL pipelines, data warehouses, analytics platforms, or distributed data systems. - Regular use of AI coding agents such as Cursor, Claude Code, Codex, Windsurf, Gemini CLI, or similar tools. - Ability to evaluate model-generated data infrastructure and pipeline implementations. - Preferred: Experience operating large-scale data platforms. Requirements - $400 per accepted task. - Compensation is tied to accepted work. Application Process - Upload resume - AI interview based on your resume - Submit form Resources & Support - For details about the interview process and platform information, please check: https://talent.docs.mercor.com/welcome - For any help or support, reach out to: support@mercor.com - PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.