Senior Product Data Engineer
New
Flexibility to work from anywhere in Europe, significant overlap with Eastern European working hoursFull-TimeSenior
Salary not disclosed
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Job Details
- Experience
- 5+ years
- Required Skills
- AWSETLMachine LearningAirflowSparkScalaDatabricksPySpark
Requirements
- 5+ years of experience in data engineering, backend engineering, or large-scale distributed systems development.
- Strong hands-on expertise with Spark technologies, including PySpark, Scala, or Databricks environments.
- Proven experience building and maintaining production-grade ETL/ELT pipelines and large-scale data processing platforms.
- Strong understanding of unstructured data processing, workflow orchestration tools, and cloud-native architectures.
- Practical experience with AWS services such as EMR, Glue, Lambda, ECS, S3, Athena, or similar technologies.
- Experience shipping end-to-end product features from planning and architecture through deployment and iteration.
- Familiarity with LLM-powered systems, AI-driven search, embeddings, or machine learning workflows in production environments.
- Strong system design skills with a focus on scalability, reliability, and maintainability.
- Comfortable working autonomously in distributed teams with excellent communication and collaboration skills.
Responsibilities
- Design, develop, and scale customer-facing data products that transform raw social media signals into reliable insights and APIs.
- Build and optimize large-scale ETL/ELT pipelines and distributed data processing systems using technologies such as Spark, Airflow, AWS, and GCP.
- Develop intelligent systems capable of extracting creator demographics, collaborations, interests, and behavioral insights from unstructured datasets.
- Contribute to AI-assisted search and recommendation capabilities using LLMs, embeddings, and modern machine learning workflows.
- Collaborate closely with engineers across Data Insights, Data Search, and Data Core teams to deliver scalable and high-performing solutions.
- Own projects from architecture and implementation to deployment, monitoring, and continuous improvement.
- Ensure system reliability, scalability, code quality, and operational efficiency while balancing performance and infrastructure costs.
- Participate in technical discussions, pair programming, and iterative product development in a highly collaborative remote-first culture.
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