
Tech Lead Data Engineer @ SambaTV
1 day ago
- 5+ years of experience in Data Engineering, Software Engineering, or a related field.
- Must-have expertise in Apache Airflow, Databricks, and PySpark for orchestration, scalable data processing, and transformation.
- Expertise in Python or strong proficiency in another modern programming language with a willingness to master Python.
- Deep understanding of distributed data processing frameworks (e.g., Apache Spark or similar).
- Strong knowledge of data modelling, database design, and query optimization for both relational and non-relational databases.
- Experience with cloud-based data infrastructure (AWS, GCP, or Azure) and modern data lake architectures.
- Familiarity with CI/CD pipelines and automation tools for data engineering.
- Proven track record of mentoring engineers and leading technical projects.
- Excellent problem-solving and communication skills, with the ability to work effectively in a distributed team environment.
Samba TV tracks streaming and broadcast video across the world with our proprietary data and technology. We are on a mission to fundamentally transform the viewing experience for everyone. Our data enables media companies to connect with audiences for new shows and movies, and enables advertisers to engage viewers and measure reach across all their devices. We have an amazing story with a unique perspective on culture formed by a global footprint of data and AI-driven insights.
As a Tech Lead - Data Engineering, you will be responsible for leading the development of scalable, high-performance data pipelines that power Samba TV's analytics and insights. You will play a critical role in designing and implementing architectural improvements, ensuring best practices, and mentoring a team of engineers. You will collaborate closely with Data Science, Analytics, and Product teams to deliver robust, production-ready data solutions that drive business impact.
,[Lead the design, development, and optimization of large-scale data pipelines and infrastructure., Architect scalable and efficient solutions for data ingestion, transformation, and storage, ensuring performance, reliability, and security., Mentor and guide engineers, fostering a culture of technical excellence and continuous improvement., Collaborate cross-functionally with Data Science, Analytics, and Product teams to translate business needs into data-driven solutions., Enhance monitoring and observability of data processes, improving debugging, error detection, and system reliability., Drive best practices for code quality, testing, and software design in data engineering.] Requirements: Spark, Airflow, PySpark, Apache Spark, PostgreSQL, Databricks, AWS, CI/CD, Terraform Tools: Jira, Bitbucket, Sonar, Agile, Scrum. Additionally: Sport subscription, Private healthcare, Flat structure, Lunch card, Small teams, International projects, Dodatkowe dni wolne, Bike parking, Free snacks, Free beverages, Free lunch, Free parking, Startup atmosphere, Modern office.-
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