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# Sr Data Architect

- **Company:** ApTask
- **Location:** New York, NY, United States
- **Experience:** Expert
- **Salary:** $166,400.0 - $176,800.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Airflow, Amazon Web Services, Application Integration Architecture, Automation of Tests, Cloud Database, Continuous Integration, Data as a Services, Data Architecture, Data Governance, Data Mapping, Data Security, Metadata, Performance Tuning, Data Ingestion, Sql Optimization, Snowflake, Informatica Cloud, Integration Frameworks, Apache Kafka, Data Management, Restful APIs
- **Published:** October 17, 2026
- **Apply:** https://www2.jobdiva.com/portal/?a=4ujdnwqsdebu7m13em5f0pt5dw80o500d7dv9cbq5ebzngb7yk0n43mjtefnbx0d&compid=0/jobs/29468279#/jobs/29468279

## About the Role

* Strong expertise in Snowflake architecture, advanced SQL, performance optimization, and secure data-sharing patterns.
 * Strong expertise in AWS cloud architecture and data services.
 * 12+ years in enterprise data architecture or cloud data-platform delivery.
 * Experience with dbt, Airflow, SnapLogic or similar integration tools, Kafka, REST APIs, and CI/CD.
 * Experience with data governance, metadata, lineage, access controls, and data quality frameworks such as SODA.
 * Strong stakeholder communication and experience leading onsite and offshore technical teams.
 * Ability to work onsite in Dallas three days per week.

## Description

* Lead the architecture and technical design of enterprise cloud data platforms.
 * This role combines architecture ownership with hands-on guidance for delivery teams and close collaboration with business, product, governance, and engineering stakeholders., * Own end-to-end architecture for data ingestion, transformation, data products, APIs, governance, security, observability, and application integration.
 * Design scalable Snowflake data architectures, including Bronze, Silver, and Gold layers, data models, and reusable onboarding patterns.
 * Define AWS-based integration, security, performance, reliability, and deployment patterns.
 * Guide source-to-target mapping, data modeling, data quality, lineage, metadata, access controls, and production- readiness decisions.
 * Lead architecture reviews, resolve technical risks, and ensure consistency across onsite and distributed engineering teams.
 * Provide hands-on direction for CI/CD, automated testing, regression protection, monitoring, production support, and optimization.