Analytics - Lead Data Architect

Practice: Analytics

Position Title: Lead Data Architect

Position Location: Remote

Reports to: Director, Data Modernization

Job Summary:

The Lead Data Architect is responsible for leading a team in designing data infrastructure to extract and organize data for authorized individuals to access. Their duties include identifying a company's internal and external data sources, collaborating with department heads to determine their data storage and organizational needs, and using the information to create and maintain data infrastructure for company employees.

Essential Functions:

• Support technical presales activities (e.g. client calls, demos, scoping, estimation)
• Deliver on consulting projects, often acting as Tech Lead providing technical guidance and expertise to project staff.
• Analyze and organize raw data.
• Build data systems and pipelines.
• Evaluate business needs and objectives.
• Conduct complex data analysis and report on results.
• Prepare data for prescriptive and predictive modeling. Combine raw information from different sources. Design enterprise-level data architectures to support analytics, BI, and data science use cases.
• Define and implement data strategy, standards, and frameworks for data integration, storage, and consumption.
• Collaborate with business and technical stakeholders to translate business needs into scalable data solutions.
• Develop data models (conceptual, logical, physical) and oversee database design and optimization.
• Lead efforts in building modern data platforms (e.g., cloud-based data lakes, warehouses, and real-time pipelines).
• Ensure data governance, data quality, security, and compliance with internal and external regulations.
• Evaluate and recommend tools and technologies to enhance the analytics ecosystem.
• Mentor data engineers, analysts, and other team members on best practices in data architecture and analytics.

Required Skills/Abilities/Competencies

• Excellent verbal and written communication skills.
• Ethical and Critical Thinking
• Excellent interpersonal and customer service skills.
• Excellent sales and customer service skills.
• Excellent organizational skills and attention to detail.
• Excellent time management skills with a proven ability to meet deadlines.
• Strong analytical and problem-solving skills.
• Strong supervisory and leadership skills.
• Ability to prioritize tasks and to delegate them when appropriate.
• Ability to function well in a high-paced and at times stressful environment.
• Proficient with Microsoft Office Suite or related software.
• Technical expertise with data models, data mining, and segmentation techniques.
• Knowledge of programming languages
• Great numerical and analytical skills.
• Deel understanding of data and analytics architectures
  • Data warehousing / Data lake / data platforms
  • ETL design patterns
  • Data modeling
  • Business Intelligence solutions
• Experience designing and maintaining enterprise-level data architecture to support analytics, BI, and data science use cases.
• Experience defining and implementing data strategy, standards, and frameworks for data integration, storage, and consumption.
• Experience collaborating with business and technical stakeholders to translate business needs into scalable data solutions.
• Experience developing data models (conceptual, logical, physical) and overseeing database design and optimization.
• Experience leading efforts in building modern data platforms (e.g., cloud-based data lakes, warehouses, and real-time pipelines).
• Ability to ensure data governance, data quality, security, and compliance with internal and external regulations.
• Ability to evaluate and recommend tools and technologies to enhance the analytics ecosystem.
• Ability to mentor data engineers, analysts, and other team members on best practices in data architecture and analytics.
• Strong expertise in SQL, data modeling, ETL/ELT design, and API-based data integrations.

Education and Experience:

• 8+ Years experience as a data engineer or in a similar role.
• Degree in Computer Science, IT, or similar field; Master preferred
• Hands-on experience with database design.
• Focused on data platforming technologies, especially from the following vendors:
  • Microsoft (Fabric, OneLake)
  • IBM (Cloud Pak for Data)
  • Snowflake
  • Databricks
• Data integration experience including migration to the following cloud platforms:
  • Azure
  • AWS
  • Google Cloud Platform
• Relevant Data engineering certifications