Data Architect

Hiring: W2 Candidates Only

Visa: Open to any visa type with valid work authorization in the USA

Responsibilities

• 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 MuleSoft). Design secure multi account AWS topologies (VPC IAM KMS) for data workloads; enforce governance lineage and cataloging
• Platform Enablement (New Platform Buildout) 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 DevOps to run containerized data services on EKS (e.g. stream processors microservices connectors) and automate with CI/CD.
• Data Integration & Processing Guide ingestion patterns: Kafka topics/partitions retention compaction schema evolution (Avro/Protobuf) DLQ strategies.
• Architect MuleSoft 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.

Requirements:

• 8 years in data architecture/engineering with 3 years architecting on AWS.
• Proven design of S3âbased data lakes with robust partitioning lifecycle policies and metadata/catalog strategy.
• Handson experience with Kafka (topic design schema evolution consumer groups throughput/latency tuning).
• Practical MuleSoft 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.

Preferred Qualifications:

• 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 DevOps practices for data (pipeline CI/CD environment promotion GitOps).
• Prior work enabling self service analytics and establishing an enterprise semantic layer. Tools & Technologies (Environment) AWS: S3 EKS Athena IAM KMS CloudWatch Glue/Lake Formation (as applicable).
• Streaming & Integration: Kafka ( Schema Registry) MuleSoft. Warehouse & BI: Snowflake Tableau.
• Data Formats: Parquet/ORC/Avro/Protobu; partitioning/bucketing best practices.
• Observability & Quality: Metrics lineage DQ checks and alerting (tooling per org standard).