Data Architect; Local to Texas

We are seeking a hands ‘on Data Architect to design and evolve an AWS‘based data platform”spanning streaming ingestion (Kafka), API/enterprise integration (Mule Soft), containerized data services (EKS), data lake on S3, interactive query with Athena, and analytics/reporting on Snowflake and Tableau.

You will set data architecture standards, lead solution design, and guide engineering teams to deliver a scalable, secure, and cost ‘efficient platform that accelerates product and analytics use cases.

• Architecture & Design:
  Own the end to end data architecture across ingestion, storage, processing, serving, and visualization layers. Define canonical data models and domain data contracts; lead conceptual/logical/physical data modeling and schema design for batch and streaming use cases.
• Establish reference architectures and patterns for event driven and API ‘led data integration (Kafka, Mule Soft). Design secure, multi ‘account AWS topologies (VPC, IAM, KMS) for data workloads; enforce governance, lineage, and cataloging.
• Platform Enablement (New Platform Build‘out):
  Lead the blueprint and incremental rollout of a new AWS data platform, including landing ât raw ât’ curated zones on S3, Athena for ‘hoc/interactive SQL, and Snowflake for governed analytics and reporting.
• Define platform SLAs/SLOs, cost guardrails, and chargeback/showback models; optimize storage/compute footprints.
• Partner with Dev Ops to run containerized data services on EKS (e.g., stream processors, microservices, connectors) and automate with CI/CD.
• Architect Mule Soft APIs/flows for system to ‘system data exchange and orchestration; standardize API contracts and security. Define Athena query strategies, partitioning, file formats (Parquet/ORC), and table metadata practices for performance/cost. Set patterns for CDC, bulk/batch ETL/ELT, and stream processing; select fit purpose transformation engines.
• Analytics, Reporting & Self ‘Service:
  Shape a semantic layer and governed Snowflake models (data vault/star schemas) to serve BI and data science. Enable business teams with Tableau dashboards, certified data sources, and governance for KPI definitions and refresh cadences.
• Security, Governance & Quality:
  Implement data classification, encryption, access controls (RBAC/ABAC), masking/tokenization, and audit trails.
• Establish data quality standards, SLOs, observability (freshness, completeness, accuracy), and automated validation.
• Leadership &
  
  Collaboration:
  
  Provide architecture runway, backlog guidance, and technical mentorship for data engineers, API/streaming engineers, and BI developers.
• Partner with Product, Security, and Compliance to align roadmaps, standards, and delivery milestones.
• Produce decision records, diagrams, and guidance that make complex designs easy to adopt.

• 8+ years in data architecture/engineering with 3+ years architecting on AWS.
• Proven design of S3–based data lakes with robust partitioning, lifecycle policies, and metadata/catalog strategy.
• Hands‘on experience with Kafka (topic design, schema evolution, consumer groups, throughput/latency tuning).
• Practical Mule Soft integration design (API ‘led connectivity, RAML/OAS, policies, governance).
• Production experience with Amazon EKS for data/streaming microservices and connectors.
• Strong SQL and performance tuning with Athena; expertise selecting file formats/partitioning for cost/perf.
• Data warehousing on Snowflake (ELT, clustering, resource monitors, security) and delivering analytics via Tableau.
• Mastery of data modeling (3NF, dimensional/star, data vault), data contracts, and event modeling.
• Solid foundations in security, IAM/KMS, networking for data platforms, and cost management.

• Experience with schema registries, stream processing frameworks, and change data capture.
• Background in data governance (catalog/lineage), metadata automation, and compliance frameworks.
• Familiarity with and Dev Ops practices for data (pipeline CI/CD, environment promotion, Git Ops).
• Prior work enabling self ‘service analytics and establishing an enterprise semantic layer.

• AWS: S3, EKS, Athena, IAM, KMS, Cloud Watch, Glue/Lake Formation (as applicable).
• Streaming & Integration:
  Kafka (+ Schema Registry), Mule Soft.
• Warehouse & BI:
  Snowflake, Tableau.
• Observability & Quality:
  Metrics, lineage, DQ checks, and alerting (tooling per org standard).