Technical Lead Data (TGQF)

What you'll do • Collaborate with architects and contribute to the design of new data products and services by proposing robust, scalable solutions aligned with organizational needs. • Participate in the implementation of the target data architecture and drive its adoption across teams. • Serve as the subject matter expert for all topics related to data, data architectures, and data processing pipelines. • Provide technical leadership and expertise across all Quality Foundations products regarding data storage, modeling, governance, and processing. • Define, maintain, and promote data standards and best practices within QF, ensuring their consistent application across teams. • Propose, review, and validate technical and architectural decisions through Architecture Decision Records (ADRs), and ensure adoption of approved decisions. • Actively contribute to the development and delivery of initiatives involving the highest levels of complexity or risk. • Advise architects, project managers, and leaders on technology directions and opportunities to improve data platforms. • Analyze and optimize the performance, cost efficiency, reliability, and scalability of data systems. • Act as a subject matter expert in relational and non-relational database optimization. • Collaborate with development, analytics, artificial intelligence, and operations teams to ensure seamless integration of data solutions. • Ensure the technical quality of data pipelines and promote best practices in monitoring, alerting, and operations. • Foster knowledge sharing, mentorship, and the development of technical autonomy within data development teams. • Participate in the technical evaluation of new technologies, platforms, and data-related approaches. • Perform any other related duties as required. What you'll bring to the team Education • Bachelor's degree in Computer Science, Computer Engineering, Software Engineering, or an equivalent field of study. Relevant Experience • Minimum of 8 years of experience in software development or data engineering. • Significant experience designing and implementing large-scale data platforms. • Experience in technical leadership, team coaching, or mentorship. • Experience with distributed architectures and large-scale data processing systems. Skills and Knowledge • Technical Expertise • Strong expertise in large-scale data solution development and SQL/NoSQL data modeling. • Strong proficiency in one or more of the following languages: Python, PySpark, SQL, and Scala . • Solid understanding of modern data architectures, data processing pipelines, and analytics platforms, including Medallion architectures (Bronze/Silver/Gold) and Lakehouse platforms (Databricks, Delta Lake). • Experience designing configurable and environment-agnostic solutions (development, staging, production), including pipeline-as-code and configuration management practices. • Ability to design scalable, high-performance, and maintainable solutions. • Experience documenting architectural and technical decisions. Technical Assets • Knowledge of cloud services ( AWS, Azure, or equivalent ) as well as Docker and Kubernetes technologies. • Knowledge of data orchestration frameworks such as Apache Airflow or Databricks Workflows . • Knowledge of real-time data streaming technologies ( Spark Structured Streaming or equivalent). • Knowledge of Databricks, Apache Spark (batch and streaming), Delta Lake, Elasticsearch/OpenSearch, SQL Server, and PostgreSQL . • Knowledge of large-scale data platform administration and both relational and non-relational databases. • Knowledge of monitoring, logging, and alerting systems for data pipelines. • Understanding of machine learning and artificial intelligence concepts. • Experience working in high-volume, real-time critical systems environments (telemetry, observability, monitoring) is considered a significant asset. Professional Competencies • Excellent analytical and problem-solving skills. • Strong ability to solve co