Sr Data Architect

JOB DESCRIPTION

The Sr. Enterprise Architect is responsible for creating data architectures and models to make a better application fabric business to support the business. The person will not only work closely with colleagues in IT and various departments within the lines of business to understand operations and model a wide variety of data assets, but even more importantly, devise strategies and plans to enable better data management using modern database, data warehouse and data lake technologies to ensure that the company meets industry and data modeling best practices. This is a manager level position for an individual with a strong background in dimensional modeling who likes working with data and solving data and architecture problems at scale.
This exciting data architecture role will have the opportunity to partner with Business Analysis, Data Engineering, Data Science, and business colleagues to ensure proper data stewardship and semantic consistency of data across multiple disciplines and lines of business operations.
Nature & Scope-Principal Areas of Responsibilities:
Create or improve existing data pipelines in cloud for data transformation and aggregation, data analytics, visualization and data science use cases
Drive data integration efforts to increase value of operational technology investments including AMI, Water Quality, Customer Experience, SCADA, GIS, Asset Management, Work Management, IIoT, etc.
Collaborate closely with Data Engineering and Data Science teams to identify performance bottlenecks in data models and queries then develop and implement solutions
Address technical inquiries around enterprise architecture and general features / functionality of Snowflake data lake platform
Contribute to and help in the execution of the data management roadmap and support of a vision for information delivery and management including the data migration, security design and data pipeline best practices
Identify and determine solutions for new systems being implemented
Provide architecture guidance in the interaction with business users and migration teams to plan, develop, improve and maintain complex data tier technology standards
Contribute to the optimized design and operation of a Snowflake-on-AWS data lake environment
  
Core Requirements
At a minimum, a bachelor   s degree in Computer Science, Information Technology or a related field is required. An MBA or Master   s Degree is an advantage.
5 to 10 years' experience in a senior-level IT management role
Strong communication and customer engagement skills
Project management skills, including concurrently contributing to or managing multiple projects
Professional and ethical behavior
Experience leading significant data architecture transformations at a technical level within a large organization
Deep experience in data architecture, data modeling and implementing data lakes
True, "Hands- On" history of architecting, designing, and building enterprise-class relational and dimensional data models for large data lakes/data reservoirs
  
Additional Skills/Abilities Needed:
Skilled in Data Modelling (Dimensional, Normalized, Key-value pair), Information Architecture, Analytics, Schema Evolution, Data Organization Layouts
Familiarity with a variety of project management methodologies including Agile and Waterfall
Proficient in designing data infrastructure for data lakes
Advanced knowledge of SQL and related programming languages (PL/SQL, T-SQL, Python)
Experience in Full BI life cycle of Data Warehousing and Data Integration projects from design to development to operational support
Skilled in strategies in how to best protect and secure data in databases, warehouses, and lakes
Experience with cloud infrastructure, storage optimization and query optimizations
Familiar with technologies including Snowflake, BladeBridge, ETL/ELT tools, Fivetran, Mulesoft, SCADA, Oracle/SQL Server, AWS, ESRI GIS, INFOR EAM, KloudGin
Develop source, target, and output mapping technical documents as required for data lineage and transformation and integration
Familiarity with data structures (i.e. 3NF, 2NF, OLAP, OLTP, Star & Snowflake)
Ability to design slowly changing dimension
Familiar with creating solution strategies for dealing with Unknown, Not Applicable, Non conforming attribute values.
Design knowledge of surrogate key management real time data processing
  
  
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