Staff Data Architect

Staff Data Architect

Requirements

• 7+ years’ experience in database management, dimensional modeling, IT systems and Big Data & AI/ML engineering experience.
• Deeply technical and analytical with implementation and architectural experience in Data Warehousing, Customer 360 modeling, Streaming, and Big Data, AI/ML engineering.
• Strong hands-on experience and proficiency in using Databricks as a Data Lakehouse and in dbt.
• Hands-on experience leading large-scale database, ETL/ELT deployment in batch or streaming ingestion, and AI/ML projects with building feature software.
• Experience with data migration techniques and process planning.
• AWS Certification such as AWS Solutions Architect or AWS Certified Big Data.
• Strong experience in data security/compliance experience, or equivalent.
• Strong problem-solving skills, including optimizing new processes.
• Ability to influence multiple teams, functional areas, and levels of leadership.
• Ability to see around corners, predict needs, and identify patterns.
• Ability to manage multiple priorities in a fast-paced environment.
• Excellent leadership, communication, presentation, and facilitation skills are necessary.
• Strong analytical and problem-solving skills.
• Bachelor’s degree in computer science, or a related field.

Responsibilities

• Partner with the rest of the Data Architecture team to lead the development and execution of the data architecture roadmap, aligning with the organization’s overall data strategy and business objectives.
• Lead and contribute to Customer 360 modeling efforts by integrating diverse customer data sources to create a unified view of the customer.
• Define data models, standards, and governance policies to ensure consistent and high-quality data across the organization.
• Design data products that utilize Databricks as the primary data warehouse solution and leverage dbt for data modeling and transformations.
• Identify and evaluate emerging technologies and trends in data management and analytics, recommending strategic adoption to enhance data capabilities, particularly those that support Customer 360 objectives.
• Design and implement scalable and maintainable data pipelines and data platforms, leveraging cloud platform tools and technologies.
• Partner with data engineers, product managers and other stakeholders to translate business requirements into technical solutions, bridging the gap between strategy and execution.
• Oversee the performance and optimization of data systems, constantly seeking ways to improve efficiency and cost-effectiveness.
• Foster a collaborative environment within the data engineering team, promoting knowledge sharing and continuous learning.
• Effectively communicate the value and impact of data architecture to various stakeholders, ensuring alignment and buy-in.
• Advocate for and secure resources to support the ongoing development and maintenance of the data infrastructure.

Preferred Qualifications

No preferred qualifications provided.