- Azure
- Big data
- Data modeling
- Data warehouse and datalakes
- Business acumen
- Data security
- Architect data security model
- Identify where they are acquiring data, loading data, staging data
- What data to transform and how to do it
- Build the consumption layer
- Data subject layer
- Visualization layer
- Foundational layer on governance
Requirements
- Defining the future data architecture and operating model based on modern thinking including data mesh, lake house, domain driven architecture and using UX techniques to uncover high value user journeys
- Develop a deep understanding of the business domain and enterprise technology inventory to craft a solution roadmap that achieves business enablement, maximizes reuse, and protects the ecosystem
- Contribute to designing multi-phased cloud data strategies, including crafting multi-phased implementation roadmaps
- Architect solutions for Performance, Availability, Reliability, Security & Cost
- Develop a comprehensive data architecture capable of supporting various data types (structured, semi-structured, unstructured) and analytics needs from reporting to machine learning
- Provide a standard common business vocabulary, express strategic requirements, outline high-level integrated design to meet those requirements, and align with enterprise strategy and related business architecture
- Collaborate with business, product, and technology teams early in product lifecycle to influence end-to-end architecture, including functional and non-functional aspects with a keen eye for data quality, data integrity and data availability
- Create strategies for data transformations and analysis for clinical, image, device, wearable, and demographic data
- Evaluate and implement a variety of data tools (Python, SQL, NoSQL, Talend, Snowflake/Synapse) on Azure to build ETLs/ELTs and data models
- Drive proofs-of-concept initiatives, rapid prototyping with the intent of validating hypotheses.
- Research and evaluate the best-of-breed technologies to inform data architecture decisions, build-vs-buy, and cost/benefit analysis
- Drive platform automation to promote continuous integration/continuous delivery, test-driven development, and streamlined production deployment frameworks
- Drive collaborative reviews of design, code, data, features implementation to drive engineering excellence around total cost of ownership, data quality & process maintainability
- Collaborate to design, implement, & assess solutions & procedures to be compliant with data governance policies and standards
- Write clear, detailed, concise documentation—architecture diagrams, reference architecture, data flows, data models, design, and implementation plan
- Share insights and best practices with Engineering team, provide technical mentorship to the Engineering team
- Able to clearly articulate breadth of topics such as Cloud Data Warehouses, Data Lake technologies, ETL, Data modeling, Machine Learning & DevOps
Minimum Experience/Skills/Competencies:
- 10+ years' experience with large-scale, distributed data pipelines, as well as data management, storage, and modeling techniques (Kimball, 3NF, Star Schema, Dimension modeling, Data Marts, Operational Data Stores, Data Vault 2.0 a plus).
- Minimum 2 years of working experience as a Data Architect on Data Analytics projects using Snowflake and Azure (preferred), AWS or GCP
- Experience in Data Migration from RDBMS to cloud data warehouse preferably Snowflake
- Proven understanding of data governance, data quality, reusable frameworks, and decision support systems design principles
- Proven track record of collaboration with technology leaders and business partners to drive impact
- In-depth, hands-on experience using structured and unstructured data as well as key data technologies, including Azure, Snowflake, Talend, Airflow, Kafka, Spark, etc.
- Experience with data security and data access controls and design
- Excellent written and verbal communication skills
- Ability to prioritize multiple tasks in a fast-paced environment
- Being comfortable with a big vision, lots of ambiguity and shifting priorities
- Strong critical thinking skills matched with the ability to articulate solutions to other team members.