About this role
This is a remote position.
Role Overview
We are looking for a Senior / Principal Data Architect to take technical ownership of a privacy-preserving data platform that enables organizations to securely transform and prepare operational data for AI/ML training and analytics without compromising individual privacy.
You will be responsible for designing scalable data architecture, establishing engineering standards, and driving technical decisions across data ingestion, processing, governance, privacy, security, and platform optimization. The role requires strong hands-on experience with AWS data lake/lakehouse technologies and a deep understanding of data privacy and compliance.
Key Responsibilities
- Design and lead the architecture of a scalable, secure, and cost-efficient AWS data lake/lakehouse platform using services such as Amazon S3, AWS Glue, Athena, Lake Formation, and related AWS data services.
- Define data architecture patterns for batch and real-time/CDC ingestion from transactional and operational systems.
- Design efficient Parquet-based data layouts, including partitioning strategies, file sizing, compaction, compression, and query optimization.
- Architect and implement data de-identification, tokenization, anonymization, and privacy-preserving techniques for sensitive datasets.
- Establish data governance frameworks covering data ownership, access control, classification, lineage, cataloging, retention, and auditability.
- Design robust data catalog and metadata management solutions while supporting schema evolution and data discovery.
- Define and enforce data quality, security, privacy, and compliance standards across the platform.
- Collaborate with Data Engineering, AI/ML, Security, Privacy, Legal, and Compliance teams to translate business and regulatory requirements into technical solutions.
- Optimize data platforms for performance, scalability, freshness, reliability, and cloud cost efficiency.
- Establish architecture and engineering best practices for teams building and consuming data products.
- Provide technical leadership and mentorship to data engineers and other technical stakeholders.
- Evaluate new technologies and architectural approaches to improve the platform's capabilities and support evolving AI/ML requirements.
Requirements
Required Skills & Experience
- 8+ years of experience in Data Engineering, Data Architecture, or related roles.
- 3+ years of experience designing and owning data platforms used by multiple engineering or analytics teams.
- Strong hands-on experience designing and implementing AWS data lake/lakehouse architectures.
- Strong knowledge of Amazon S3, AWS Glue, Amazon Athena, and AWS Lake Formation.
- Strong understanding of data modeling, data warehousing, data lakes, and lakehouse architectures.
- Hands-on experience with Parquet, partitioning, file optimization, compaction, and large-scale data processing.
- Experience designing CDC and batch data ingestion pipelines from transactional systems.
- Strong understanding of data cataloging, metadata management, data lineage, and schema evolution.
- Practical experience with data privacy, anonymization, de-identification, tokenization, or other privacy-preserving techniques.
- Strong understanding of data governance, access control, security, compliance, and regulatory requirements.
- Experience working directly with Privacy, Legal, Security, or Compliance teams.
- Strong understanding of data quality, data lifecycle management, and data retention.
- Experience with cloud cost optimization and performance engineering for large-scale data platforms.
Nice to Have
- Experience with GDPR, NDPA/DPA, or similar data privacy regulations.
- Knowledge of k-anonymity, differential privacy, or privacy-preserving analytics.
- Experience with synthetic data generation for AI/ML or analytics use cases.
- Experience with Apache Iceberg or other open table formats.
- Experience supporting AI/ML training data pipelines and feature engineering platforms.
- Experience with AWS security and identity services, including IAM and KMS.
- Experience with large-scale data cost optimization and FinOps.
- Experience designing multi-account or multi-environment AWS data platforms.
- Familiarity with infrastructure automation using Terraform or CloudFormation.
- Experience establishing data platform standards, reference architectures, and technical governance.
Required Skills
Data Architecture | Data Engineering | AWS | Amazon S3 | AWS Glue | Amazon Athena | AWS Lake Formation | Data Lake / Lakehouse | Data Modeling | Parquet | CDC | Data Ingestion | Data Catalog | Data Lineage | Schema Evolution | Data Governance | Data Privacy | Data De-identification | Data Anonymization | Data Tokenization | Data Security | Data Quality | AI/ML Data Platforms | Performance Optimization | Cloud Cost Optimization
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