Senior AWS DataLake Architect
First seen by Alion on Nov 12, 2026. Semtech scores A on the Alion truth index.
Job Summary :
The Senior AWS Data Lake Architect is responsible for designing, building, and scaling the organizations AWS-based data lake platform, with a strong focus on enabling AI and machine learning solution deployment. This role owns the end-to-end architecture of the data lake ecosystem - from ingestion and storage through governance and consumption - and partners closely with data science and AI engineering teams to operationalize AI models in production. The role also provides technical leadership and mentorship across the data engineering function.
Responsibilities :
- Architect, design, and implement scalable, secure AWS data lake solutions (Amazon S3, AWS Lake Formation, AWS Glue, Amazon EMR, Amazon Redshift, Amazon Athena, Amazon Kinesis/MSK), including reference architecture, data zoning, partitioning strategy, and schema/catalog management (25%).
- Lead the design and deployment of AI/ML-ready data pipelines, including feature stores and model training pipelines, and integrate with Amazon SageMaker and Amazon Bedrock to support generative AI and machine learning use cases (20%).
- Partner with data science and AI engineering teams to operationalize AI solutions in production, including model deployment pipelines, MLOps integration, and inference data flows (15%).
- Establish and enforce data governance, security, and compliance standards, including IAM, KMS encryption, Lake Formation permissions, and audit logging (15%).
- Drive cost optimization and performance tuning across storage, compute, and query layers, and evaluate new AWS services and architectural patterns (15%).
- Provide technical leadership and mentorship to data engineers, own technical documentation and architecture decision records, and support operational handoffs for production issues (10%).
Minimum Qualifications:
- Bachelor's degree in Computer Science, Information Systems, Engineering, or related field required; Master's degree preferred.
- 8+ years' experience in data engineering or data architecture required; 5+ years specifically architecting solutions on AWS required.
- Hands-on experience designing and operating AWS data lake architectures, including Amazon S3, AWS Lake Formation, AWS Glue, Amazon EMR, Amazon Redshift, Amazon Athena, and Amazon Kinesis/MSK.
- Demonstrated experience deploying or supporting AI/ML solutions in production, including integration with Amazon SageMaker and Amazon Bedrock.
- Proficiency in Python and/or Scala/Spark for large-scale data processing.
- Strong understanding of data governance, security, and compliance best practices in cloud environments.
Desired Qualifications :
- AWS Certified Data Engineer - Associate (DEA-C01) or equivalent AWS certification (e.g., AWS Certified Solutions Architect - Professional).
- Experience with modern lakehouse formats such as Apache Iceberg, Delta Lake, or Apache Hudi.
- Experience architecting generative AI solutions on AWS using Amazon Bedrock, including foundation model access, agents, and knowledge bases.
- Exposure to infrastructure-as-code (Terraform, AWS CloudFormation, or AWS CDK) for provisioning data platform resources.
- Experience operating in regulated or large-scale enterprise environments with strict data governance requirements.
Skills
DataLake, AWS, AI Integration, Data Engineering, Machine Learning, Python, Scala, Spark, Data Governance, Solution Architect, AWS Bedrock