Sr Data Architect

Job Description

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