Lead Data Engineer

Lead Data EngineerAbout you A hands-on technical expert and team leader who blends deep expertise in modern data engineering technologies with a passion for mentoring and collaboration.This leader not only architects and oversees scalable, resilient data infrastructure, but also cultivates a culture of learning and innovation among junior engineers—encouraging the adoption of best practices and cutting-edge tools.With a strong sense of partnership, they proactively engage with data scientists to surface overlooked data assets, clarify data lineage, and ensure analytical work is built on solid, well-understood foundations.Equal parts strategist and enabler, they drive both technical excellence and cross-functional alignment in data-driven organizations.CORE JOB FUNCTIONS/RESPONSIBILITIES: Interpersonal soft responsibilities as team leader:- Tracks the various Machine learning projects and their data needs.- Tracks and improves Kanban process of product maintenance- Drives complex technical discussions both within company and outside data partners- Actively Contributes to the design of machine learning solutions by having a deep understanding of how the data is used and how new sources of data can be introduced- Advocates for investments in tools and technologies to streamline data workflows and reduce technical debt- Continuously explores and adopts emerging technologies and methodologies in data engineering and machine learning Technical competencies and responsibilities- Develops and maintains scalable data pipelines to support machine learning models and analytics- Collaborates with data scientists to ensure efficient data processing and model deployment- Ensures data quality, integrity, and security across all stages of the data pipeline- Implements monitoring and alerting systems to detect anomalies in data processing and model performance- Enhances data versioning, data lineage, and reproducibility practices to improve model transparency and auditing.Knowledge.Education.Experience Required- 5+ years of experience in data engineering or related fields, with a strong focus on building scalable data pipelines to support machine learning workflows.- Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or other relevant fields.- Specific experience in Kafka needed.Snowflake and data bricks would be huge plus.- Proven expertise in designing, implementing, and maintaining large-scale, high-performance data architectures and ETL processes managing 1TB a day.- Strong knowledge of database management systems (SQL and NoSQL), distributed data processing (e.g., Hadoop, Spark), and cloud platforms (AWS, GCP, Azure).- Experience working closely with data scientists and machine learning engineers to optimize data flows for model training and real-time inference with latency requirements.- Hands-on experience with data wrangling, data preprocessing, and feature engineering to ensure clean, high-quality data for machine learning models.- Solid understanding of data governance, security protocols, and compliance requirements (e.g., GDPR, HIPAA) to ensure data privacy and integrity.Preferred- Experience in data pipelines and analytics for video-game development- Experience in Advertising industry- Experience in online businesses where transactions happen without human intervention.Tipo de puesto: Tiempo completoSueldo: $60,****** - $70,****** al mesTipo de jornada:- Turno de 8 horasEscolaridad:- Licenciatura terminada (Deseable)Experiência:- Data engineering: 5 años (Obligatorio)- ETL: 5 años (Deseable)- Kafka: 3 años (Deseable)Idioma:- Inglés (Deseable)Lugar de trabajo: Empleo presencial