Principal AWS Data Architect

Principal AWS Data Architect

Location: Remote

Job Summary

We are seeking a highly experienced Principal Data Architect to lead the architecture and modernization of a large-scale enterprise data platform built primarily on AWS . This is a senior-level role requiring someone who can operate as both a strategic architect and a hands-on technical leader.

The ideal candidate will have extensive experience designing modern cloud data platforms, leading data modernization and lift-and-shift initiatives , establishing data governance and DataOps practices, and building scalable data lakehouse architectures using AWS services.

You will work closely with engineering, architecture, and business stakeholders to define the future-state data platform while ensuring scalability, reliability, security, governance, and cost optimization.

Key Responsibilities

Data Architecture & Cloud Modernization

• Lead the architecture and modernization of enterprise-scale data platforms on AWS.
• Develop strategic roadmaps for migrating legacy data warehouse and data processing environments to modern AWS architectures.
• Design scalable data lake and lakehouse architectures supporting large-volume data processing.
• Drive lift-and-shift and modernization initiatives while minimizing operational and business disruption.
• Design solutions that provide flexibility and reduce unnecessary vendor lock-in.
• Evaluate emerging AWS data technologies and recommend appropriate solutions based on business and technical requirements.

AWS Data Engineering & Platform Architecture

• Architect and oversee solutions using AWS Glue, EMR/EMR Serverless, S3, Redshift , and related AWS services.
• Design highly scalable ETL/ELT pipelines and enterprise data processing frameworks.
• Establish architecture patterns for batch, streaming, and high-frequency data ingestion.
• Optimize data storage, processing, query performance, scalability, and AWS cloud costs.
• Provide technical direction on data modeling, data integration, orchestration, and platform engineering.

Data Governance & DataOps

• Establish enterprise-wide data governance standards, policies, procedures, and architectural guidelines.
• Implement DataOps practices to improve development quality, reliability, and operational efficiency.
• Establish automated quality controls such as data validation, schema management, testing, and CI/CD quality gates.
• Define standards for data security, metadata, lineage, data quality, and lifecycle management.
• Develop reusable frameworks and architectural guardrails to reduce technical debt and improve engineering consistency.

Leadership & Mentorship

• Serve as the senior technical authority for enterprise data architecture and platform decisions.
• Mentor senior and intermediate data engineers and architects.
• Provide technical guidance on architecture, coding standards, data modeling, and cloud best practices.
• Partner with engineering leadership and business stakeholders to translate business requirements into scalable technical solutions.
• Influence technical decisions across teams without relying solely on organizational authority.

Required Qualifications

• 20+ years of overall IT/data engineering experience , preferably within large-scale or Fortune 500 environments.
• Extensive experience as a Principal Data Architect, Enterprise Data Architect, Staff Architect, or equivalent senior technical leader .
• Strong hands-on expertise with AWS data services and cloud architecture .
• Proven experience leading large-scale data modernization, migration, and lift-and-shift initiatives .
• Strong experience designing enterprise data lake/lakehouse architectures .
• Deep experience with:
  • AWS Glue
  • Amazon S3
  • Amazon Redshift
  • Amazon EMR / EMR Serverless
• Strong understanding of ETL/ELT, data pipelines, data integration, and data modeling .
• Experience implementing data governance, DataOps, data quality, and engineering standards .
• Strong knowledge of cloud security, scalability, performance optimization, and cost management.
• Ability to balance strategic architecture with hands-on technical execution .
• Excellent communication, stakeholder management, and technical leadership skills.

Preferred Qualifications

• Experience with Google Cloud Platform (GCP) or other cloud platforms.
• Multi-cloud or cloud-agnostic architecture experience.
• Experience with Apache Iceberg, Delta Lake , or other open table formats.
• Experience with Fivetran or similar enterprise data replication/CDC technologies.
• Experience with Oracle Fusion Cloud, Oracle ERP , or other large enterprise source systems.
• Strong Python and SQL development experience.
• Experience with Spark/PySpark and distributed data processing.
• Experience with dbt, Great Expectations, SQLFluff , or similar DataOps/data quality technologies.
• Experience with Kimball, Data Vault 2.0 , or other enterprise data modeling methodologies.
• Experience designing architectures that support advanced analytics, AI, and modern BI platforms.

Ideal Candidate

The ideal candidate is a hands-on Principal-level AWS Data Architect who can take ownership of an enterprise data modernization initiative from strategy through execution. They should be comfortable defining architecture and governance standards while also diving into technical details, mentoring engineering teams, and solving complex data-platform challenges.

Core Keywords: AWS | Data Architecture | Data Lakehouse | AWS Glue | EMR | EMR Serverless | S3 | Redshift | Data Governance | DataOps | ETL/ELT | Data Pipelines | Data Modernization | Lift & Shift | Data Migration | Python | SQL | Spark | Fivetran | Apache Iceberg | Data Modeling | Cloud Architecture | Enterprise Architecture | Multi-Cloud