Technical Lead / Solution Architect

Role Overview

Data Analysis and BI

• Analyze enterprise and sports-related systems to identify improvements and optimize performance; profile data for trends, anomalies, and quality issues.
• Develop analytical models and curated datasets; build and maintain ETL/ELT pipelines from applications, databases, APIs, files, sensors, and third-party platforms.
• Maintain dashboards, semantic models, and analytical products; optimize pipelines and queries, validate outputs, and promote self-service analytics.

Integration and Application Support

• Integrate third-party applications with internal systems and work with application teams and vendors to resolve interoperability issues.
• Troubleshoot sports-related applications, deliver system updates and user training, and maintain enterprise platforms and application reliability.

Governance and Collaboration

• Support sports science and athlete performance analytics; develop models for data warehouses, data lakes, and Lakehouse environments.
• Maintain data profiling, validation, reconciliation, quality controls, metadata, lineage, documentation, ownership, access, privacy, and retention practices.
• Gather stakeholder requirements, coordinate technical workstreams and deliverables, and contribute to planning, design, testing, implementation, production support, and knowledge transfer.
• Track project work and documentation using JIRA and Confluence.

Experience and Education

• 10–12 years in data analysis, data engineering, BI, data platform delivery, or a related discipline.
• Bachelor's degree in Computer Science, Information Systems, or a related field.
• Hands-on experience with data pipelines, source integration, analytical modelling, dashboards, or data products.
• Advanced SQL and Python or a comparable programming language.

Technical Requirements

• Understanding of ETL/ELT, APIs, orchestration, data warehouses, data lakes, Lakehouse architectures, and relational and non-relational databases.
• Experience with data modelling, query optimization, data visualization, and BI tools; knowledge of data quality, metadata, lineage, security, and governance.
• Familiarity with source control, CI/CD, testing, monitoring, and DataOps or DevOps; proficiency in JIRA, Confluence, and technical documentation.

Preferred Certifications and Experience

• Relevant certifications in data engineering, cloud data platforms, analytics, or BI are preferred, including Azure, AWS, Google Cloud, Microsoft Fabric, Databricks, or Power BI.
• CBAP or PMP certifications are advantageous.
• Experience in sports, athlete performance, venue, event, or facility systems; enterprise application and sensor integrations; and enterprise-scale data platforms is preferred.
• Experience coordinating technical projects with business stakeholders, architects, developers, infrastructure teams, and vendors is preferred.