Senior Data Platform Architect: Azure & Databricks

Stryker

Flower Mound (TX)

On-site

USD 136,000 - 271,000

Full time

2 days ago

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Benefits offered by this job

Health insurance

Dental insurance

Vision insurance

401(k) plan

Employee Stock Purchase Plan (ESPP)

Job summary

Stryker is seeking a Principal Architect for EDT Data Platform Engineering to translate enterprise data architecture into scalable Azure and Databricks solutions. You will partner with delivery teams, business representatives, and data stewards to build governed data pipelines, analytics-ready models, and reusable automation that improves consistency across projects and teams.

The role requires hands-on delivery on Azure and Databricks, strong knowledge of data governance, CI/CD, IaC, and the

Qualifications

Bachelor's degree in CS/Engineering/IS or related field.
Minimum 8 years of experience in data engineering, data warehousing, and analytics platforms with hands-on Azure and Databricks experience.
Experience with Azure Data Factory, Azure Data Lake Storage, Azure SQL, Databricks Delta Live Tables, Delta Lake, Spark, Workflows, and Unity Catalog.
Advanced experience with PySpark or Python and SQL, including batch and streaming pipeline design.
Experience with Azure DevOps pipelines, repositories, policies; PowerShell automation; CI/CD; and Infrastructure as Code.
Experience with schema enforcement, data contracts, data quality frameworks, metadata-driven design, monitoring, debugging, and performance tuning.

Responsibilities

Build and maintain ingestion frameworks using Azure Data Factory, Databricks, and Spark.
Implement Bronze-to-Silver transformations with data quality checks, schema validation, and data contract rules.
Optimize batch and streaming pipelines for performance and cost.
Own CI/CD pipelines in Azure DevOps and automate project onboarding, including repositories, pipelines, policies, and templates.
Maintain Infrastructure as Code and automation using Terraform, PowerShell, and Python; troubleshoot pipeline failures and permission issues.
Design curated Gold-layer data models, including star and snowflake schemas, fact tables, dimensions, surrogate keys, and slowly changing dimensions.
Align reusable models, KPI definitions, and business logic with the enterprise semantic layer in Power BI, Microsoft Fabric, and downstream tools.
Manage model changes through impact analysis, backward compatibility, regression support, and documented column derivation logic.
Implement Unity Catalog standards, naming conventions, metadata policies, data quality frameworks, and role- and attribute-based access controls.
Translate high-level architecture into low-level designs, reusable templates, and engineering playbooks.
Guide delivery teams through onboarding, debugging, and design reviews.
Create reusable assets and hands-on guidance that build engineering capability and reduce repeat questions.
Assess complex data systems, identify patterns, and recommend practical solutions.