Identify, collect, and integrate data to build high-quality analytics pipelines.
Develop and optimize code to run pipelines at low cost and easy maintenance.
Build monitoring procedures and tools to ensure solid ETL and data quality.
Design processes and tools to correct ETL incidents.
Consult analytics teams to ensure best practices on data usage.
Design data architectures and support cloud data migrations.

🎯 Requirements

Experience in data engineering, big data, BI, or data science.
Spark, Python, Scala, or similar.
Excellent SQL skills enabling large-scale data transformation and analysis.
Cloud data warehousing, pipelines and ETL; Dataflow, Looker, DBT, EMR, Airflow.
Experience with cloud-based data infrastructures (GCP preferred; AWS or Azure ok).
Programming in Python or JavaScript.
Expertise in managing databases, including performance tuning, backup, and recovery.
Data quality management: profiling, cleansing, and validation.

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