Description

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, Client, 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)
• Containerization expertise (Docker/ECS)
• Infrastructure automation (Terraform, CloudFormation)
• Security compliance frameworks for AWS GovCloud environments

Key Skills

Education

Bachelor's degree