Data Architect

Position Overview:

We are currently seeking a skilled Data Architect with data modeling experience to join the Data Engineering team. The ideal candidate will have a strong foundation in data architecture, with a keen ability to design, implement, and manage data models that support our organization's needs. This role involves collaborating with data scientists, analysts, and IT team members to ensure our data structures are optimized for efficiency, scalability, and reliability.

Key Responsibilities:

• Develop and maintain conceptual, logical, and physical data models that align with business objectives and data governance standards.
• Design and implement data models that effectively support business processes and decision-making.
• Collaborate with stakeholders to understand business requirements and translate them into data models.
• Optimize data architectures for both operational and analytical purposes to improve performance and scalability.
• Deliver working solutions including data pipelines, worksheets, snowflake environments, Snow SQL, and Python automation code as required as an individual contributor while also providing leadership and best practices to other team members following your design and development best practices.
• Provide solid data modeling and architecture best practices for modern data warehousing solutions, including leveraging traditional Kimball/Inmon best practices where necessary along with Data Vault and similar approaches where possible.
• Ensure data integrity and quality by developing and implementing data governance and validation processes.
• Stay abreast of industry trends and advancements in data modeling techniques and technologies, recommending improvements to our practices as appropriate.
• Work closely with data engineers and IT personnel to implement and refine data models within our data warehousing and business intelligence environments.
• Provide technical guidance and support to team members on best practices in data modeling and data architecture.
• Must be proficient in Oracle and SQL coding (with recent experience) –Minimum of 5 years.
• Must be proficient in OLTP/3NF (Online transaction processing, 3rd normal form) as well as dimensional/data mart modeling (star schema, snowflake) – Minimum of 5 years.
• Must be proficient in data analysis and SQL skills – Minimum of 5 years.
• Experience with SDLC / Scaled agile delivery frameworks for data warehouse projects – minimum of 5 years.
• Experiences in Data modeling in Snowflake Database, Oracle Database, and in Salesforce
• Experience in Snowflake database profiling, creating, advising and reviewing data models for our data warehouse as well as data mart areas.
• Should be able to provide design of the table structures with proper data analysis and mapping capabilities.
• Will be responsible for changing, maintaining the data models and be able to work closely with the business team to understand the requirements and provide guidance on the design to the development team.
• Maintain documentation of data models, data dictionaries, and related metadata to ensure clarity and consistency across the organization.
• Should be able to assist both developers and testers to ensure that data processing is accurate, efficient, and complete.
• Should be able to prioritize work activities to meet the timelines.

Qualifications:

• Bachelor’s degree in computer science, Information Technology, Data Science, or a related field.
• Proven experience as a Data Modeler or in a similar role, with a strong portfolio of data architecture and modeling projects.
• Proficient in data modeling tools and technologies, with a deep understanding of relational and non-relational database systems.

• Strong analytical skills with the ability to solve complex problems and translate business requirements into technical solutions.
• Excellent communication and collaboration skills, with the ability to work effectively with both technical and non-technical stakeholders.
• Familiarity with data governance, data quality management, and data security practices.
• Knowledge of SQL, NoSQL, ETL processes, and business intelligence platforms.