Technical Lead Data (TGQF)

• Bachelor’s degree in Computer Science, Computer Engineering, Software Engineering, or an equivalent field of study.

• 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.

What you'll bring to the team

• 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.
• 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.
• Excellent analytical and problem-solving skills.
• Strong ability to solve complex technical challenges.
• Aptitude for mentoring and fostering technical autonomy within teams.
• Strong appreciation for configuration-driven approaches, including parameterized systems, declarative pipelines, and reproducible deployments (Infrastructure as Code).
• Excellent communication skills and ability to explain complex technical concepts to diverse audiences.
• Influential leadership and the ability to drive adoption of best practices across teams.
• Ability to work effectively in a multidisciplinary environment.
• Strong initiative and autonomy.
• Results-oriented mindset with a focus on continuous improvement.
• Ability to manage multiple priorities simultaneously and make sound prioritization decisions.