IC5 - Data Architect

Objective of the Role:

• As a Technical Data Architect (IC5), you will be the visionary and strategic leader shaping our global data and AI architecture strategy. You will define the technical direction for the organization's data ecosystem, ensuring it scales to meet long-term business goals. Operating in a highly autonomous environment, you will champion technical excellence, innovation, and total ownership, balancing strategic vision with a hands-on approach to problem-solving. Additionally, you will act as a key Spin Culture Ambassador, driving institutional values, fostering a collaborative, elite engineering culture, and mentoring the next generation of technical leaders. 

 

Main Responsibilities:

Strategic & Enterprise Architecture 

• Enterprise Data Strategy: Define, evolve, and execute a comprehensive enterprise data and AI architecture roadmap aligned with long-term business and product goals.  

• Innovation & Future-Proofing: Drive cutting-edge innovation in data frameworks, emerging big data technologies, and AI-driven data solutions to maintain a competitive edge.  

• Data Integration & Ecosystem Governance: Oversee and design global integration patterns for highly diverse, massive-scale data sources, ensuring absolute consistency and seamless data flows across the entire organization.  

Technical Leadership & Governance 

• High-Impact Mentorship: Provide strategic technical guidance, career development, and mentorship to Lead Data Engineers, Data Model Leads, DataOps Leads, and other senior technical staff.  

• Global Standards & Documentation: Establish, institutionalize, and enforce company-wide data architecture standards, design patterns, and comprehensive technical documentation.  

• Data Quality & Governance Frameworks: Architect and oversee enterprise-level data governance and data quality frameworks to guarantee data democratization with absolute accuracy, security, and compliance.  

• Core Data Governance & Code Review: Act as the ultimate technical gatekeeper for core database structures; creating, enforcing, and reviewing data schemas, new database columns, tables, and complex queries to guarantee maximum optimization, indexing efficiency, and performance. 

1. Solution Engineering & Performance Optimization 

• Next-Gen Solution Design: Next-Gen Solution Design: Spearhead the conceptualization, architectural design, and technical proof-of-concepts (PoC) of complex, large-scale data systems, including cloud-native data lakes, mesh architectures, advanced ETL/DTL pipelines, and real-time streaming engines. 

• Extreme Performance & Scalability: Define the strategy for monitoring, auditing, and optimizing hyper-scale data systems for maximum performance, reliability, and cost-efficiency.  

• Cross-Functional Collaboration: Partner closely with executive stakeholders, product leaders, and engineering directors to translate complex business needs into robust, scalable technical architectures.  

• Database Administration (DBA) & High-Availability Replication: Design, direct, and execute high-availability data replication strategies between heterogeneous database engines (e.g., Oracle to cloud-native systems like Amazon Aurora), while overseeing advanced operational DBA and tuning tasks. 

1. Culture & Organizational Excellence 

• Autonomous Culture Champion: Cultivate and scale a high-trust, autonomous work environment that promotes extreme ownership, proactive problem-solving, and continuous technical improvement.  

• Spin Culture Ambassador: Actively foster a diverse, inclusive, and dynamic technical community within the company, aligning engineering practices with Spin’s core values. 

 
  

Required Knowledge and Experience:

• Experience: 7+ years of proven experience in Data Architecture, Enterprise Data Engineering, and/or AI Systems Architecture (with a track record of leading architectural transformations at an enterprise level).  

Technical Skills 

• Expert Data Modeling: Master-level proficiency in relational/non-relational database design, advanced SQL, complex DTL/ETL architectural patterns, and data mesh concepts. Deep expertise in RDBMS performance tuning, query optimization, indexing strategies, and database migration (specifically Oracle to AWS Aurora setups). 

• Hyper-Scale Streaming & Real-Time Data: Deep experience designing production-grade, ultra-low latency real-time data architectures (e.g., advanced integration between AWS Kinesis/Kafka and Databricks).  

• Cloud & Big Data Platforms: Extensive expertise with multi-cloud or deep single-cloud setups (AWS, GCP, Azure) and distributed computing technologies (Databricks, Spark, Hadoop, Delta Lake).  

• AI & Machine Learning Data Infrastructure: Robust experience architecting data pipelines and infrastructure specifically tailored for machine learning (MLOps), LLMs, and AI-driven applications.  

Soft Skills & Leadership 

• Strategic Influence: Exceptional ability to influence both technical teams and non-technical executives without direct authority. 

• Problem Solving & Communication: Elite analytical skills coupled with outstanding communication, presentation, and collaboration abilities.  

• Proactive Innovation: A relentless drive for continuous learning and the ability to instill that passion into the engineering organization.  

Preferred Qualifications 

• Industry Certifications: Enterprise Architecture certifications (e.g., TOGAF) or Professional/Expert-level cloud certifications (AWS Certified Data Engineer, Databricks Solutions Architect, etc.).  

• Data Governance Expertise: Deep knowledge of international compliance standards (GDPR, CCPA, etc.) and data privacy architecture.  

• English Level: Bilingual / Advanced.