Enterprise Data Architect
We are looking for an Enterprise Data Architect to join our team. The data architect is responsible for designing, creating, and managing an organization’s data architecture. This role is critical in establishing a solid foundation for data management within an organization, ensuring that data is organized, accessible, secure, and aligned with business objectives. The data architect designs warehouses, file systems and databases, and defines how data will be collected and organized.
Key elements of this role include:
- 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 implements database management systems that meet the organization’s 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 and implements processes for the ETL process from various sources into the organization’s 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.
These skills will make you successful:
Education:
- A bachelor’s 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:
- Strong 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.