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Lead Cloud Data Engineer

Job in San Francisco, San Francisco County, California, 94102, USA
Listing for: Akraya
Full Time position
Listed on 2026-07-30
Job specializations:
  • IT/Tech
    Data Engineering, AWS, Cloud Computing: Infrastructure & Operations
Salary/Wage Range or Industry Benchmark: 90 - 100 USD Hourly USD 90.00 100.00 HOUR
Job Description & How to Apply Below
Position: Lead Cloud Data Engineer : 26-02136

Lead Cloud Data Engineer – Data Mesh & AI

Primary

Skills:

AWS Data Engineering (Expert), Data Mesh Architecture (Expert), Databricks & Modern Data Platforms (Expert), Dev Sec Ops  & Infrastructure as Code (Advanced), AI-Augmented Data Engineering (Advanced)

Contract Type: W2 Only Duration: 18+ Months

Location:

San Francisco, CA (Hybrid) Pay Range: $90 - $100 on W2

Job Summary:

We are seeking a Lead Cloud Data Engineer – Data Mesh & AI to lead the design, development, and modernization of enterprise-scale data platforms supporting large data warehouse and data hub initiatives. The ideal candidate will have deep expertise in AWS data engineering, Data Mesh architecture, Databricks, Dev Sec Ops , and AI-driven engineering practices. This role will drive the implementation of scalable data products, federated governance, and AI-augmented solutions while providing technical leadership across cross-functional engineering teams.

Key Responsibilities
  • Design, develop, and maintain scalable ETL/ELT pipelines using AWS services including Glue, EMR, Lambda, Kinesis, Step Functions, Redshift, and S3.
  • Architect and implement enterprise Data Mesh solutions with domain-oriented ownership, federated governance, and reusable self-service data product frameworks.
  • Develop modern data platforms leveraging Databricks, Delta Lake, Unity Catalog, Starburst/Trino, Collibra, and Immuta.
  • Implement enterprise data governance, metadata management, data lineage, access controls, and automated data quality monitoring frameworks.
  • Build and maintain CI/CD pipelines, Infrastructure as Code (Terraform/Cloud Formation), containerized deployments, and Dev Sec Ops  automation.
  • Design and implement AI-powered solutions including RAG pipelines, agentic AI workflows, Amazon Bedrock, LLM integrations, and AI-assisted SDLC automation.
  • Optimize cloud infrastructure for scalability, security, performance, and cost efficiency across hybrid cloud environments.
  • Provide L3 production support, mentor engineering teams, and establish best practices for modern data engineering and Data Mesh adoption.
  • Lead technical architecture reviews, collaborate with business stakeholders, and translate business requirements into scalable technical solutions.
  • Create and maintain technical architecture documentation, implementation standards, and engineering best practices.

Must-have

Skills:

  • 8+ years of experience in Data Engineering with at least 5+ years designing enterprise AWS Data Platforms.
  • Strong hands-on experience with AWS S3, Glue, EMR, Redshift, Lambda, Kinesis, Lake Formation, and Step Functions.
  • Proven experience implementing Data Mesh architecture, domain-driven data products, and federated governance.
  • Expertise with Databricks (Delta Lake, Unity Catalog), Starburst/Trino, Collibra, and Immuta.
  • Strong knowledge of ETL/ELT development, data modeling, metadata management, data lineage, and data quality frameworks.
  • Experience with Terraform, Cloud Formation, Docker, ECS, Git Hub Actions/Git Lab CI, Jenkins, and Dev Sec Ops  best practices.
  • Experience implementing AI-enabled engineering solutions using Amazon Bedrock, LLMs, RAG architectures, Copilot, Claude Code, or similar AI frameworks.
  • Strong SQL, Python, and cloud-native data engineering expertise.
  • Experience supporting secure, compliant cloud environments, including AWS Gov Cloud or regulated environments.
  • Excellent leadership, mentoring, architecture design, communication, and stakeholder management skills.

Nice-to-have

Skills:

  • Experience supporting enterprise data warehouse modernization initiatives.
  • Knowledge of hybrid cloud and on-premises data platform integration.
  • Experience implementing self-service analytics and reusable data product frameworks.
  • Familiarity with cost optimization strategies for large-scale cloud data platforms.
  • Experience working within highly regulated industries such as Financial Services or Government.

Preferred Qualifications:

  • Bachelor's or Master's degree in Computer Science, Data Engineering, Information Systems, or a related technical field.
  • AWS Certifications (Solutions Architect, Data Analytics, or Developer) preferred.
  • Experience leading enterprise-scale cloud modernization and AI…
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