3 days ago
Gurgaon, IndiaStaff+
Responsibilities
- Define solution architecture direction, standards, reference architectures, design patterns, and reusable components for complex data and analytics initiatives.
- Own architecture diagrams, technical design documents, integration blueprints, data models, standards, and architecture decision records.
- Develop proof-of-concepts, reference implementations, and reusable implementation patterns for data platforms and analytics solutions.
- Evaluate emerging technologies, platforms, frameworks, and advanced analytics capabilities for architectural and business fit.
- Conduct architecture, design, code, and technical quality reviews covering scalability, performance, security, reliability, and supportability.
- Embed data privacy, access control, governance, and compliance requirements into solution designs.
- Partner with engineering teams to resolve complex performance, quality, scalability, reliability, integration, and operational challenges.
- Mentor engineers and architects through solution design, implementation planning, and delivery reviews.
- Translate strategic requirements into technical designs, phased implementation plans, and delivery roadmaps with product, platform, governance, and business stakeholders.
- Influence technical direction across multiple teams through hands-on technical leadership and expertise without direct management authority.
Requirements
- 10+ years of experience in data engineering, solution architecture, or technical design roles, including significant architecture ownership.
- Demonstrated experience architecting large-scale enterprise data platforms and integration solutions.
- Deep expertise in enterprise data architecture, including data warehousing, Lakehouse, and real-time streaming architectures.
- Strong hands-on experience with cloud data platforms, data modeling, modern data architecture patterns, Databricks or equivalent Lakehouse platforms, and engineering practices.
- Strong proficiency in SQL and Python, along with data engineering concepts including ETL/ELT, CDC, dimensional modeling, star-schema design, medallion architecture, distributed data processing, and workload optimization.
- Experience designing governed data products across bronze, silver, and gold layers with lineage, data quality controls, reconciliation, and semantic consumption layers.
- Experience designing analytics, reporting, semantic model, and business intelligence architectures, including Power BI semantic models, DAX, row-level security, refresh patterns, and performance optimization.
- Experience with enterprise integration patterns, ERP ecosystems, API-based integration, and event-driven architectures.
- Experience with infrastructure-as-code, observability, performance optimization, and DevOps practices in cloud-native data platforms.
- Familiarity with data governance, metadata management, and master data management frameworks.
- Ability to balance scalability, performance, cost, maintainability, strategic architecture, and practical delivery constraints.
- Excellent written and verbal communication skills, including presenting architecture recommendations and trade-offs to senior technical and business stakeholders.
Benefits
- Hybrid work arrangement.
- Approximately 10% travel.
Tech Stack
Categories
Data Engineering
About Stryker
Stryker designs and manufactures medical devices and equipment for hospitals and surgeons, spanning orthopaedic implants, trauma and spine hardware, surgical tools, endoscopy, navigation, and patient care equipment. The NYSE-listed company, founded in 1941 and headquartered in Kalamazoo, Michigan, sells products and related services worldwide to health systems and ambulatory centers. It reported $22.6 billion in 2024 sales and markets its portfolio across roughly 75 countries.