Data Platform Software Engineer – Lead (USC or GC) (W2 Only)

NOTE: Only USC and GC or GC EAD please (Onsite Role)

Please share your updated resumes to srikanth@cloudingest.com

Role: Data Platform Software Engineer – Lead

Department: Data Centre of Excellence (Data COE)

Location: Seattle, WA (Onsite)

Duration: Long Term

Rate: DOE

Experience: 15+ Years

Role Overview

We are seeking an experienced Data Platform Software Engineer – Lead to drive the architecture, engineering, and governance of our enterprise-scale data platform. This leadership role within the Data COE is responsible for building a modern, scalable, and governed data ecosystem across AWS and Azure, enabling secure, reliable, and high-performance data access while establishing enterprise engineering standards.

Key Responsibilities

• Design, build, and evolve enterprise data platforms using Snowflake and Databricks across AWS and Azure.
• Develop and maintain scalable ETL/ELT pipelines leveraging Apache Spark, Python, SQL, dbt, Airflow, and Kafka.
• Define enterprise standards for data ingestion, transformation, storage, governance, and consumption.
• Implement data quality, lineage, metadata management, and data contract best practices.
• Manage cloud storage architecture using Amazon S3 and Azure Data Lake Storage (ADLS).
• Lead containerized platform deployments using Kubernetes and implement CI/CD pipelines using GitHub Actions or equivalent.
• Collaborate with cross-functional engineering teams to drive platform architecture and governance.
• Conduct architecture reviews, mentor engineering teams, and establish platform engineering best practices.

Required Qualifications

• 15+ years of overall IT experience with 8+ years in Data Engineering.
• 3+ years leading enterprise Data Platform or Staff Engineer initiatives.
• Expert-level experience with:
• Snowflake (Data Modeling, Performance Tuning, RBAC, Dynamic Data Masking, Zero-Copy Cloning/Sharing)
• Databricks (Delta Lake, Unity Catalog, Cluster Management, Workflows)
• Apache Spark
• Python & SQL (Scala is a plus)
• Apache Kafka
• Apache Airflow
• dbt
• Strong expertise in AWS (S3) and Azure (ADLS).
• Experience with Kubernetes, CI/CD, GitHub Actions, Infrastructure Automation.
• Strong understanding of distributed data processing, governance, and enterprise platform architecture.

Preferred Qualifications

• Great Expectations or similar Data Quality frameworks.
• Feature Store technologies (Feast, Tecton).
• Data Catalog tools (DataHub, Amundsen).
• Apache Iceberg and Lakehouse Architecture.
• Schema Registry and Data Contracts.
• BigQuery integrations and multi-cloud platform experience.

Desired Skills

• Enterprise Data Platform Architecture
• Cloud Data Engineering
• Platform Governance & Standards
• Data Quality & Lineage
• Leadership & Technical Mentorship
• Strong stakeholder management and communication skills
• Ownership mindset with focus on scalability, reliability, and cost optimization.