Technical Lead Data (TGQF)

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.

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.