• 5+ years of hands-on experience working with large-scale data systems in production environments.
• Proven experience designing, deploying, and integrating big data frameworks such as PySpark, Kafka, Databricks, or equivalent cloud-based data platforms.
• Strong expertise in Python and SQL, with experience building and optimizing data processing workflows (batch and/or streaming).
• Experience with AWS cloud services and Linux-based environments.
• Background in building ETL/ELT pipelines and orchestrating workflows end-to-end.
• Understanding of event-driven and domain-driven design principles in modern data architectures.
• Experience preparing data for BI, analytics, and consumption by product teams or platforms.
• Familiarity with infrastructure-as-code tools (e.g., Terraform) — advantage.
• Experience with parquet, delta table format, Debezium, or AWS-native data solutions — advantage.
• Experience in data modeling, data analysis, or supporting visualization/analytics teams — advantage.
• Familiarity with data visualization tools or creating dashboards — advantage.
• Experience supporting machine learning or algorithmic applications — nice to have.
• BSc or higher in Computer Science, Engineering, Mathematics, or another quantitative field.

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