Senior Data Platform Engineer
WaferWire Cloud Technologies
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Benefits offered by this job
Job summary
WaferWire Technology Solutions (WCT) is seeking a Senior Data Platform Engineer in Austin to design, build, and operate enterprise cloud data capabilities. You will lead data pipelines, Bronze-Silver-Gold architecture, and scalable platform components with focus on security, cost, and reliability, while mentoring engineers.
The role covers development and operations with ~70% development and ~30% production support, including RBAC, governance, and observability.
Qualifications
- Bachelor's degree in computer science, Information Systems, Engineering, Data Science, or a related field.
- Master's degree preferred.
- 10+ years of experience in data engineering, data warehousing, or data platform engineering.
- 5+ years of experience designing or implementing cloud-based data warehouse, data lake, or data platform solutions.
- 3+ years of hands-on Azure Databricks experience in enterprise production environments.
- Experience with ETL/ELT development, data modeling, large-scale integration, and cloud platform modernization.
- Experience leading technical implementations, solution design, design reviews, and production releases.
- Experience supporting production environments, incident response, root cause analysis, and operational support processes.
- Experience in regulated, financial services, banking, or audit-sensitive environments preferred.
- Advanced proficiency in SQL, Python, PySpark, and Spark performance optimization.
- Strong experience with Azure Databricks, Delta Lake, Unity Catalog, Databricks Workflows, and Delta Live Tables.
- Strong understanding of lakehouse, Medallion Architecture, dimensional modeling, data warehousing, and analytics-oriented data structures.
- Experience with Azure DevOps, Git, CI/CD, automated testing, and deployment practices; Databricks Asset Bundles experience preferred.
- Experience implementing data quality, validation, reconciliation, monitoring, metadata, lineage, governance, and security controls.
- Strong technical leadership, solution design, analytical, troubleshooting, and problem-solving skills.
- Ability to independently lead complex work from design through production support and balance innovation with reliability, security, cost, and supportability.
- Excellent collaboration, mentoring, documentation, and communication skills across technical and business teams.
- Experience with Power BI, MicroStrategy, MDM, streaming architectures, infrastructure automation, or AI-assisted development preferred.
- Databricks Data Engineer certification at the Associate or Professional level preferred.
Responsibilities
- Design, develop, and maintain scalable data pipelines, ingestion frameworks, transformation processes, and reusable data products using Azure Databricks, PySpark, SQL, and Delta Lake.
- Implement Bronze, Silver, and Gold architecture patterns supporting enterprise reporting, analytics, AI, and self-service data consumption.
- Build reusable frameworks, utilities, and platform components that improve engineering productivity, quality, consistency, and deployment speed.
- Develop and support batch, near-real-time, and streaming integration solutions, including modernization of legacy warehouse and ETL workloads.
- Serve as technical lead for complex initiatives; develop solution designs, lead technical reviews, recommend tools and approaches, and guide work through production implementation.
- Partner with data architects and platform leaders to ensure solutions are scalable, secure, governed, cost-conscious, and operationally supportable.
- Mentor engineers and promote standards for coding, testing, documentation, performance, and production readiness.
- Implement data quality, validation, reconciliation, monitoring, metadata, and lineage capabilities; support RBAC and enterprise security controls.
- Build and maintain CI/CD, automated testing, deployment, and release processes using Azure DevOps and Git-based practices.
- Contribute to platform observability, alerting, operational dashboards, health metrics, performance tuning, and cost optimization.
- Participate in production support, incident response, pager, and on-call rotations; troubleshoot issues, lead root cause analysis, and implement durable remediation.
- Create and maintain operational runbooks, support procedures, technical documentation, and knowledge-sharing assets.
- Collaborate with architecture, governance, security, analytics, application, and business teams to translate requirements into scalable platform solutions.
- Support technical discovery, estimation, roadmap planning, delivery execution, and evaluation of emerging cloud, data, and AI capabilities.
Skills
Education
Tools
Job description
WaferWire Technology Solutions (WCT) specializes in delivering comprehensive Cloud, Data and AI solutions through Microsoft's technology stack. Our services include Strategic Consulting, Data/AI Estate Modernization, and Cloud Adoption Strategy. We excel in Solution Design encompassing Application, Data, and AI Modernization, as well as Infrastructure Planning and Migrations. Our Operational Readiness services ensure seamless DevOps, ML Ops, AI Ops, and Sec Ops implementation. We focus on Implementation and Deployment of modern applications, continuous Performance Optimization, and future-ready innovations in AI, ML, and security enhancements. Delivering from Redmond-WA, USA, Guadalajara, Mexico and Hyderabad, India, our scalable solutions cater precisely to diverse business requirements and multiple time zones (US time zone alignment).
The Senior Data Platform Engineer is a senior individual contributor responsible for designing, developing, enhancing, and supporting enterprise cloud data platform capabilities. Reporting to the Sr. Director of Data Platform Transformations & Operations, this role combines hands-on engineering, solution design, and operational ownership to deliver scalable, secure, and reliable solutions. The engineer serves as a technical lead on major initiatives while remaining accountable for production support and operational excellence.
The role supports platform transformation and steady-state operations, with approximately 70% focused on development of new capabilities and 30% on operations, support, and platform reliability. Primary areas include Azure Databricks, cloud data engineering, platform modernization, automation, governance, and continuous improvement.
- Design, develop, and maintain scalable data pipelines, ingestion frameworks, transformation processes, and reusable data products using Azure Databricks, PySpark, SQL, and Delta Lake.
- Implement Bronze, Silver, and Gold architecture patterns supporting enterprise reporting, analytics, AI, and self-service data consumption.
- Build reusable frameworks, utilities, and platform components that improve engineering productivity, quality, consistency, and deployment speed.
- Develop and support batch, near-real-time, and streaming integration solutions, including modernization of legacy warehouse and ETL workloads.
- Serve as technical lead for complex initiatives; develop solution designs, lead technical reviews, recommend tools and approaches, and guide work through production implementation.
- Partner with data architects and platform leaders to ensure solutions are scalable, secure, governed, cost-conscious, and operationally supportable.
- Mentor engineers and promote standards for coding, testing, documentation, performance, and production readiness.
- Implement data quality, validation, reconciliation, monitoring, metadata, and lineage capabilities; support RBAC and enterprise security controls.
- Build and maintain CI/CD, automated testing, deployment, and release processes using Azure DevOps and Git-based practices.
- Contribute to platform observability, alerting, operational dashboards, health metrics, performance tuning, and cost optimization.
- Participate in production support, incident response, pager, and on-call rotations; troubleshoot issues, lead root cause analysis, and implement durable remediation.
- Create and maintain operational runbooks, support procedures, technical documentation, and knowledge-sharing assets.
- Collaborate with architecture, governance, security, analytics, application, and business teams to translate requirements into scalable platform solutions.
- Support technical discovery, estimation, roadmap planning, delivery execution, and evaluation of emerging cloud, data, and AI capabilities.
- Bachelor's degree in computer science, Information Systems, Engineering, Data Science, or a related field.
- Master's degree preferred.
- 10+ years of experience in data engineering, data warehousing, or data platform engineering.
- 5+ years of experience designing or implementing cloud-based data warehouse, data lake, or data platform solutions.
- 3+ years of hands-on Azure Databricks experience in enterprise production environments.
- Experience with ETL/ELT development, data modeling, large-scale integration, and cloud platform modernization.
- Experience leading technical implementations, solution design, design reviews, and production releases.
- Experience supporting production environments, incident response, root cause analysis, and operational support processes.
- Experience in regulated, financial services, banking, or audit-sensitive environments preferred.
- Advanced proficiency in SQL, Python, PySpark, and Spark performance optimization.
- Strong experience with Azure Databricks, Delta Lake, Unity Catalog, Databricks Workflows, and Delta Live Tables.
- Strong understanding of lakehouse, Medallion Architecture, dimensional modeling, data warehousing, and analytics-oriented data structures.
- Experience with Azure DevOps, Git, CI/CD, automated testing, and deployment practices; Databricks Asset Bundles experience preferred.
- Experience implementing data quality, validation, reconciliation, monitoring, metadata, lineage, governance, and security controls.
- Strong technical leadership, solution design, analytical, troubleshooting, and problem-solving skills.
- Ability to independently lead complex work from design through production support and balance innovation with reliability, security, cost, and supportability.
- Excellent collaboration, mentoring, documentation, and communication skills across technical and business teams.
- Experience with Power BI, MicroStrategy, MDM, streaming architectures, infrastructure automation, or AI-assisted development preferred.
- Databricks Data Engineer certification at the Associate or Professional level preferred.
Benefits: Medical, dental, Vision, Life, PTO, Holidays, 401(k) benefits and ancillaries may be available for eligible WCT employees and may vary depending on the nature of your employment.
WCT will accept applications and processes offers for these roles until the role is filled.
WCT is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances
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