About the Role :

We are looking for a versatile Data Architect with a strong background in designing and implementing enterprise-grade data platforms and cloud-native solutions. The role combines architecture leadership with hands-on implementation, focusing on scalable data foundations, integration patterns, governance, analytics enablement, and modern AWS services.

Responsibilities :

- Design and own end-to-end data architecture across ingestion, storage, transformation, serving layers, APIs, and cloud services.

- Define and enforce architectural standards, data modeling practices, integration patterns, and reusable platform conventions.

- Lead technical design sessions and guide development teams through implementation, code reviews, and solution reviews.

- Design cloud-native data platforms on AWS using services such as S3, Glue, Lake Formation, Athena, Redshift, Lambda, Step Functions, IAM, KMS, CloudWatch, and EventBridge.

- Collaborate with analytics and data science teams to prepare curated, trusted datasets for reporting, simulation, and advanced analytics.

- Oversee governance, security, data quality, lineage, observability, and operational controls across the data lifecycle.

- Conduct architecture reviews to ensure solutions are scalable, performant, secure, and cost-effective.

- Translate business and technical needs into clear architectural blueprints, reference implementations, and implementation guidance.

- Partner with product managers, business analysts, UX designers, engineers, and cloud teams to align technical solutions with business outcomes.

Qualifications :

- Bachelor's or master's degree in Computer Science, Engineering, or a related field.

- 12+ years of overall experience in data architecture, data engineering, or solution architecture, with at least 6 years in an architect role.

- Deep experience with AWS services and patterns for data platforms.

- Strong grounding in data modeling, ETL/ELT, data warehousing, medallion or lakehouse patterns, and API-driven integrations.

- Proficiency in SQL and at least one programming language used in data platforms such as Python.

- Experience with microservices, RESTful APIs, event-driven architectures, CI/CD pipelines, and DevOps practices.

- Solid understanding of data governance, security, access control, lineage, and data quality management.

- Strong communication skills with the ability to engage both technical and non-technical stakeholders.

- Knowledge of Databricks and Azure data services will be considered a plus.

Preferred Skills :

- Exposure to GenAI or agentic frameworks such as LangChain, CrewAI, MCP, or AWS Bedrock Agents.

- Experience with MLOps or AI/ML platforms such as SageMaker, MLflow, or Kubeflow.

- Familiarity with vector databases, prompt engineering, RAG pipelines, and intelligent workflow orchestration.

- Cloud certifications such as AWS Solutions Architect, AWS Data Engineer, or AWS Machine Learning Specialty.

- Experience with enterprise data platforms supporting analytics, operations, or distributed business sites.