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. Azure and Databricks knowledge will be considered an added advantage.
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 as appropriate.
- 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, preferably including S3, Glue, Athena, Lake Formation, Redshift, Lambda, Step Functions, IAM, KMS, CloudWatch, and EventBridge.
- 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.
