Data Engineer
5 dni temu
- Develop new data pipelines to create our TV ad impressions and viewership datasets.
- Automate existing business processes and support visualization of key datasets.
- Analyze and improve the efficiency, scalability, and stability of data collection, storage, and retrieval processes for our core systems.
- Work with data scientists, data analysts and other business partners developing tools and frameworks to support self-service analytics.
- Improve observability and monitoring of production processes by instrumenting existing code and creating services that expose the state of pipeline jobs and datasets to internal consumers.
- Focus on the performance of individual jobs in our processing pipelines; understanding the algorithms that power them and the trade-offs and bottlenecks that affect their runtime and resource consumption.
- Mentor members of other data teams who are eager to improve their software engineering skills; be a role model who exemplifies coding and software design best practices.
- 3+ years of industry experience Intermediate to advanced knowledge of Python, or mastery of another modern programming language with the strong desire to become an advanced Pythonista.
- We are a distributed team working from the Warsaw and San Francisco offices. Thus, you should have excellent communication skills, especially in written form.
- You should be comfortable working directly with Data Science and Analytics, and other internal consumers to bridge product requirements with Data Engineering.
- Excellent problem-solving skills and ability to interpret and analyze data.
- Having a strong mathematical inclination is a major plus.
- Previous experience with Apache Spark or similar large-scale data processing frameworks is also a major plus.
- Python as our primary language.
- Amazon Web Services (AWS) for compute and storage.
- Apache Spark on Databricks as our primary processing engine.
- Airflow for workflow scheduling.
- Terraform for configuration management.
- Databases: PostgreSQL, DuckDB, Elasticsearch, InfluxDB.
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