Sr Data Architect

Responsibilities

• Interprets and delivers impactful strategic plans improving data integration, data quality, and data delivery in support of business initiatives and roadmaps
• Designs the structure and layout of data systems, including databases, warehouses, and lakes
• Selects and designs database management systems that meet the organizations needs by defining data schemas, optimizing data storage, and establishing data access controls and security measures
• Defines and implements the long-term technology strategy and innovations roadmaps across analytics, data engineering, and data platforms
• Designs processes for the ETL process from various sources into the organizations data systems
• Translates high-level business requirements into data models and appropriate metadata, test data, and data quality standards
• Manages senior business stakeholders to secure strong engagement and ensures that the delivery of the project aligns with longer-term strategic roadmaps
• Simplifies the existing data architecture, delivering reusable services and cost-saving opportunities in line with the policies and standards of the company
• Leads and participates in the peer review and quality assurance of project architectural artifacts across the EA group through governance forums
• Defines and manages standards, guidelines, and processes to ensure data quality
• Works with IT teams, business analysts, and data analytics teams to understand data consumers needs and develop solutions
• Evaluates and recommends emerging technologies for data management, storage, and analytics
• Design, create, and implement logical and physical data models for both IT and business solutions to capture the structure, relationships, and constraints of relevant datasets
• Build and operationalize complex data solutions, correct problems, apply transformations, and recommend data cleansing/quality solutions
• Effectively collaborate and communicate with various stakeholders to understand data and business requirements and translate them into data models
• Create entity-relationship diagrams (ERDs), data flow diagrams, and other visualization tools to represent data models
• Collaborate with database administrators and software engineers to implement and maintain data models in databases, data warehouses, and data lakes
• Develop data modeling best practices, and use these standards to identify and resolve data modeling issues and conflicts
• Conduct performance tuning and optimization of data models for efficient data access and retrieval
• Incorporate core data management competencies, including data governance, data security and data quality

Job Requirements

Education:

• A bachelors degree in computer science, data science, engineering, or related field

Experience:

• At least five years of relevant experience in design and implementation of data models for enterprise data warehouse initiatives
• Experience leading projects involving data warehousing, data modeling, and data analysis
• Design experience in Azure Databricks, PySpark, and Power BI/Tableau

Skills:

• Ability in programming languages such as Java, Python, and C/C++
• Ability in data science languages/tools such as SQL, R, SAS, or Excel
• Proficiency in the design and implementation of modern data architectures and concepts such as cloud services (AWS, Azure, GCP), real-time data distribution (Kafka, Dataflow), and modern data warehouse tools (Snowflake, Databricks)
• Experience with database technologies such as SQL, NoSQL, Oracle, Hadoop, or Teradata
• Understanding of entity-relationship modeling, metadata systems, and data quality tools and techniques
• Ability to think strategically and relate architectural decisions and recommendations to business needs and client culture
• Ability to assess traditional and modern data architecture components based on business needs
• Experience with business intelligence tools and technologies such as ETL, Power BI, and Tableau
• Ability to regularly learn and adopt new technology, especially in the ML/AI realm
• Strong analytical and problem-solving skills
• Ability to synthesize and clearly communicate large volumes of complex information to senior management of various technical understandings
• Ability to collaborate and excel in complex, cross-functional teams involving data scientists, business analysts, and stakeholders
• Ability to guide solution design and architecture to meet business needs
• Expert knowledge of data modeling concepts, methodologies, and best practices
• Proficiency in data modeling tools such as Erwin or ER/Studio
• Knowledge of relational databases and database design principles
• Familiarity with dimensional modeling and data warehousing concepts
• Strong SQL skills for data querying, manipulation, and optimization, and knowledge of other data science languages, including JavaScript, Python, and R
• Ability to collaborate with cross-functional teams and stakeholders to gather requirements and align on data models
• Excellent analytical and problem-solving skills to identify and resolve data modeling issues
• Strong communication and documentation skills to effectively convey complex data modeling concepts to technical and business stakeholders