As a Data Architect on our Data Engineering team, you will own leading and broadening our Data Platform initiatives. Translating business requirements into technology requirements, while defining data standards and principles to support the organization’s enterprise data management framework. The Data Architect will not only lead our data architecture strategy but also build and manage a high-performing data team.

 GOBankingRates is embarking on an ambitious growth journey and we are looking for a seasoned Data Architect skilled in Cloud Platforms, Data Architecture, and Data Engineering. As a key member of the Data Engineering team, your mission will oversee the development and maintenance of our Enterprise Data Platform, which includes a cutting-edge Serverless Data Lake, a robust Cloud Data Warehouse, and essential data/application pipelines. Your role will be central to conceptualizing and creating our next-gen data platform.

The salary range for this role is $220,000- $240,000 + Bonus. Pay offered may vary within the posted range based on a number of factors including but not limited to job-related knowledge, skills, experience, and location.

HOW YOU’LL MAKE AN IMPACT

Architect and Design Data Solutions:

• Design and Develop scalable data platforms, considering business needs, industry trends using cutting edge modern data stack. Create POC when necessary to test new approaches.
• Enforce common data design patterns to increase code maintainability. Define and establish data architecture standards and best practices. Ensure the team follows the standards and
  utilizes best practices in their data design and development activities.
• Responsible for data platform performance, ensuring the system performs optimally. This includes monitoring the system, identifying performance bottlenecks, and implementing necessary improvements.
• Implement security measures to safeguard sensitive data in the cloud environment. Conduct peer code review and provide constructive feedback. Mentor and guide junior team members and stakeholders on data architecture and AWS cloud services. Encourage a culture of learning, experimentation, and innovation among team members.
• Communicate complex data concepts and strategies to non-technical stakeholders, explaining the benefits, risks, and considerations. Establish and maintain effective communication with the management, development teams, and business stakeholders.
• Develop training material and conduct training sessions to enhance the team’s understanding and proficiency in AWS cloud services and data architecture.
• Create and conduct project/architecture design review. Document the design, operation, and troubleshooting of technology platforms and procedures. Review and maintain documentation to ensure it is up-to-date, accurate, and effectively used by the team.
• Partner with team leads to identify, design and implement internal process improvements Automate manual processes, optimize data delivery, understand when to re-design architecture for greater scalability.

Team Leadership and People Management:

• Lead, mentor, and manage a team of data engineers, analysts, and other data-related staff.
• Provide guidance, feedback, and development opportunities for team members, fostering a culture of continuous improvement and technical excellence.
• Oversee team performance, manage workloads, and ensure the delivery of high-quality work on time.
• Lead the strategy for hiring, developing, and retaining top talent for the data architecture team.

WHAT YOU’LL NEED

• A minimum of 8 years of experience in data engineering, with a focus on data pipeline development, data architecture and cloud-based solutions
  
  
• Bachelor’s or master’s degree in computer science, Information Technology, Data Science, Engineering or a related field
  
  
• 8+ years of experience building, leading, and managing high-performing technical teams, including hiring and onboarding top talent.
• Proven experience designing, implementing, and managing scalable data platforms and architectures, preferably in a cloud environment (AWS).
  
  
• Experience with AWS services, including but not limited to S3, Airflow, DBT, GLUE and LAMBDA. Expert level experience in Snowflake is preferred.
  
  
• Proficient in SQL and at least one programming language such as Python, Java, or Scala.
  
  
• Familiarity with data modeling tools and techniques.
  
  
• Strong understanding of data warehousing concepts, ETL processes, data modeling, data governance, and data quality management
  Knowledge of performance tuning solving complex scalability issues on distributed platforms.
  
  
• Excellent communication skills, with the ability to effectively communicate complex data concepts to both technical and non-technical stakeholders
  Detail-oriented with excellent problem-solving skills and the ability to think strategically about business, product, and technical challenges
  
  
• Ability to work in a fast-paced, deadline-driven work environment and manage multiple tasks
  simultaneously
  
  
• Vendor management skills, with the ability to evaluate new technologies and services and
  determine their usefulness and applicability to the organization’s data strategy.