Lead Data Platform Engineer

• Support the design and implementation of the data platform, including environment setup and layered architecture standards, to promote growth and consistency.
• Provide senior technical guidance on platform changes, ensuring new data pipelines and sources align with established best practices.
• Assist with infrastructure-as-code, including cloud provisioning, configuration, RBAC, schema setup, and deployment through CI/CD pipelines.
• Develop performance and cost-management strategies such as workload optimization, warehouse sizing, resource monitoring, and cost visibility.
• Design, develop, and review ELT pipelines that ingest, transform, and curate data from structured and unstructured sources.
• Establish engineering standards for code review, testing, deployment, and documentation for both internal teams and contractors.
• Ensure operational readiness through monitoring, incident response, troubleshooting, and creating runbooks for independent platform operation.
• Implement data quality controls and drive remediation with source systems to address upstream issues.
• Translate data governance standards into platform controls, including role-based access, data classification, masking, retention policies, and audit-lineage.
• Support security and compliance requirements, including connectivity and data protection protocols.
• Collaborate with third-party delivery teams during platform build, supporting design, implementation, and knowledge transfer.
• Provide ongoing documentation, training, and coaching to internal data engineering teams for platform maintenance and extension.
• Enable self-service data consumption for BI and analytics teams by publishing governed datasets, data marts, and consumption schemas.
• Define and enforce standards for the semantic layer, ensuring consistent business definitions and data structures.
• Advise leadership on enterprise data priorities, onboarding future data sources, and preparing AI workloads.
• Partner with AI teams to curate AI-ready data assets and evaluate emerging platform capabilities, ensuring secure data handling and disposal.

• Bachelor’s degree in computer science or a related field.
• Minimum of 10 years of progressive experience in data engineering, data warehousing, or similar technical roles.
• At least 5 years of hands-on experience architecting and building on Snowflake.
• Proven experience implementing layered architecture models, infrastructure-as-code, and deploying via Git-based CI/CD workflows.
• Demonstrated experience as a technical lead or senior authority on data platforms, including setting standards and reviewing work.
• Experience with platform observability, monitoring, alerting, and operational dashboards.
• Certifications such as Snowflake (e.g., SnowPro Core or Advanced) and relevant AWS certifications preferred.
• Deep expertise in Snowflake warehouse design, RBAC, performance tuning, and cost management.
• Proficiency in Python and advanced SQL, capable of designing observability-driven pipelines.
• Experience with cloud architectures, especially AWS, utilizing tools like S3, IAM, and PrivateLink.
• Strong understanding of the end-to-end data analytics workflow, data modeling, and modern ELT patterns.
• Knowledge of data governance, security practices, data classification, lineage, and PII handling.
• Excellent problem-solving skills for large-scale data environments.
• Strong verbal and written communication skills for collaborating with technical and non-technical teams.
• Ability to work effectively with external partners and facilitate knowledge transfer.
• Service-oriented mindset with resourcefulness, responsiveness, and professionalism.

Preferred Qualifications

• Snowflake certification (e.g., SnowPro Core or Advanced) and relevant AWS certifications.
• Experience with modern data workflows involving semantic modeling and BI integration tools like Power BI.
• Familiarity with emerging platform features such as Cortex AI, Snowpark ML, and vector-based structures.
• Knowledge of data security and compliance standards related to data privacy and protection.
• Ability to diagnose and resolve complex data and platform issues in large-scale environments.

Dexian stands at the forefront of Talent + Technology solutions with a presence spanning more than 70 locations worldwide and a team exceeding 10,000 professionals. As one of the largest technology and professional staffing companies and one of the largest minority-owned staffing companies in the United States, Dexian combines over 30 years of industry expertise with cutting-edge technologies to deliver comprehensive global services and support.