Responsibilities
- Build and operate data platforms using public cloud infrastructure (AWS, GCP), Kafka, databases, and containers
- Develop data science platforms leveraging open-source software and cloud services
- Design and run ETL tools and frameworks to onboard data, define schemas, create DAG processing pipelines, and monitor data quality
- Aid in the development of machine learning frameworks and pipelines
- Manage mission-critical production services
- Perform other related duties as assigned
Qualifications & Skills
- 3+ years of relevant experience in a Data Platform Engineering role
- Strong software engineering skills with Python; additional experience in C++, Java, Go, or Rust is a plus
- Proven expertise in building ETL and stream processing tools with technologies like Kafka, Spark, Flink, or Airflow/Prefect
- Proficient in SQL and databases/engines such as MySQL, PostgreSQL, Snowflake, Redshift, or Presto
- Familiarity with data science tools (e.g., Jupyter, Pandas, Scikit-learn, PyTorch) and frameworks like MLFlow or Kubeflow
- Hands-on experience with AWS/GCP services, Kubernetes, and Linux in production environments
- Strong inclination toward automation and DevOps practices
- Capable of managing increasing data volume, velocity, and variety
- Agile, self-starter mindset with strong communication skills
- Ability to navigate ambiguity and prioritize tasks effectively
- Participation in on-call support beyond standard business hours
- Strong english Skills (B2)
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