AWS Data Lake Architect

Xavor Corporation · , , pakistan, Pakistan

We are looking for a Senior AWS Data Lake Architect to design, build, and scale enterprise-grade data lake platforms on AWS, with a strong focus on enabling AI and machine learning deployment. You will own the end-to-end architecture of our data lake ecosystem, from ingestion and storage to governance and consumption, and work closely with data science and AI engineering teams to operationalize models in production.

This is a hands-on technical leadership role. You will define best practices, mentor engineers, and drive architectural decisions that balance scalability, cost, security, and performance.

Key Responsibilities

• Architect, design, and implement scalable, secure AWS data lake solutions (S3, Lake Formation, Glue, EMR, Redshift, Athena, Kinesis/MSK) for both batch and real-time pipelines.
• Define and own the data lake reference architecture, including zoning (raw/curated/consumption), partitioning strategy, schema management, and metadata cataloging.
• Lead the design and deployment of AI/ML-ready data pipelines, including feature stores, model training data pipelines, and integration with SageMaker or equivalent platforms.
• Partner with data science and AI engineering teams to operationalize AI solutions, covering model deployment pipelines, MLOps integration, and inference data flows.
• Establish and enforce data governance, security, and compliance standards (IAM, encryption, data masking, Lake Formation permissions, audit logging).
• Drive cost optimization and performance tuning across storage, compute, and query layers.
• Provide technical leadership and mentorship to data engineers; conduct design and code reviews and set engineering best practices.
• Collaborate with product, analytics, security, and infrastructure stakeholders to translate business requirements into scalable technical designs.
• Evaluate and recommend new AWS services, tools, and architectural patterns to keep the platform current.
• Own technical documentation, architecture decision records (ADRs), and operational runbooks.
• Support operational handoffs and on-call escalation for production data lake and pipeline issues.

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Information Systems, or Engineering.
• 8+ years of experience in data engineering or data architecture, including 5+ years architecting solutions on AWS.
• Proven hands-on experience designing and operating AWS data lake architectures using:
• Amazon S3, AWS Lake Formation, AWS Glue (ETL and Catalog), Amazon EMR
• Amazon Redshift, Amazon Athena, Amazon Kinesis/MSK
• IAM, KMS, and data security/governance tooling
• Demonstrated experience deploying or supporting AI/ML solutions in production (e.g., SageMaker integration, ML-ready data pipelines, feature engineering, or MLOps workflows).
• Strong command of data modeling, ETL/ELT pipeline design, and orchestration (AWS Step Functions, Apache Airflow/MWAA).
• Proficiency in Python and/or Scala/Spark for large-scale data processing.
• Solid understanding of data governance, security, and compliance best practices in cloud environments.
• Excellent stakeholder communication skills, with the ability to explain trade-offs to technical and non-technical audiences.
• Experience leading technical design discussions and mentoring engineering teams.

Preferred Qualifications

• AWS Certified Data Engineer - Associate (DEA-C01), AWS Certified Solutions Architect - Professional, or equivalent.
• Experience with lakehouse formats (Apache Iceberg, Delta Lake, or Apache Hudi).
• Experience with generative AI architectures (RAG pipelines, vector databases, LLM integration patterns) on AWS, such as Amazon Bedrock.
• Exposure to infrastructure-as-code (Terraform, CloudFormation, or CDK).
• Experience in regulated or large-scale enterprise environments with strict data governance requirements.
• Experience with operational handoff processes: writing runbooks, defining SLAs/SLOs, and supporting production data platforms.