Job Title – Lead Cloud Data Engineer – Data Mesh & AI Location – San Francisco, CA (Onsite) Duration – 6+ Months
Job Description: Qualifications: We are seeking an experienced Lead Data Engineer to join our team and drive the development of modern data platforms and AI-augmented solutions. This role is critical to supporting ongoing operations of Large Data Warehouse, architecting the Large Data Hub , and preparing for the enterprise data mesh modernization program.
Responsibilities: Data Engineering & Pipeline Development:
Develop and maintain end-to-end ETL/ELT pipelines for data ingestion from multiple sources (databases, APIs, streaming), transformation, quality validation, data modeling, and consumption layer optimization using AWS services (Glue, EMR, Lambda, Kinesis, Step Functions)
Implement data governance policies, metadata management, data lineage tracking, fine-grained access controls, and automated data quality frameworks with validation rules, anomaly detection, and monitoring/alerting mechanisms
Data Mesh Architecture:
Design and implement Data Mesh architecture on AWS with federated governance, defining domain boundaries, data product specifications, and self-serve infrastructure patterns across Databricks, Starburst, Collibra, and Immuta platforms
Develop reusable frameworks, accelerators, and self-serve tools enabling domain teams to independently publish, discover, and consume data products while ensuring performance optimization and cost efficiency
DevSecOps & Infrastructure:
Integrate DevSecOps practices including CI/CD pipelines, infrastructure as code (Terraform/CloudFormation), automated security scanning, compliance validation, and disaster recovery strategies
AI-Augmented Development:
Design and build agentic AI solutions, RAG pipelines, and intelligent automation using LLMs, orchestration frameworks, and AI-powered development tools (Copilot, Claude Code) to enhance platform capabilities and accelerate SDLC
Technical Leadership & Collaboration:
Provide L3 technical support and mentor engineering teams on data mesh principles and modern data technologies
Collaborate with stakeholders to translate business requirements into technical solutions
Lead architecture design reviews and create comprehensive technical documentation
Required Qualifications: Data Mesh Architecture & AWS (5+ years required):
Deep experience designing distributed data architectures on AWS (S3, Glue, Lake Formation, EMR, Redshift)
Hands-on implementation of data mesh principles including domain-oriented data ownership, data as a product, and federated computational governance
Modern Data Platform Technologies:
Proficiency: Databricks (Unity Catalog, Delta Lake), Starburst/Trino (federated query), Collibra (data governance), or Immuta (dynamic data access control)
Ability to architect multi-technology solutions
DevSecOps & Infrastructure as Code:
Strong experience with CI/CD pipelines (GitLab/GitHub Actions, Jenkins)
Security compliance frameworks for AWS GovCloud environments
AI-Augmented Development & Engineering:
Demonstrated use of generative AI tools for accelerating SDLC activities including code generation, testing, and documentation
Experience designing or implementing agentic AI solutions using Amazon Bedrock or similar frameworks
Leadership & Soft Skills:
Proven ability to translate business requirements into technical solutions
Experience leading technical design sessions and mentoring engineering teams
Strong communication skills to convey complex architectural concepts to both technical and non-technical stakeholders
Experience working across hybrid cloud/on-premises environments
Applicant Notices & Disclaimers
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At SPECTRAFORCE, we are committed to maintaining a workplace that ensures fair compensation and wage transparency in adherence with all applicable state and local laws. This position's pay range is $70.00/hr - $90.00/hr.
