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Generalist software title plus broad Python/SQL data skills increases applicant density.
Core ETL, Python and SQL skills are highly transferable across industries.
Strong Python and advanced SQL required but open to recent graduates, so moderate selectivity.
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Design and build ETL/ELT data pipelines to ingest data from multiple sources including APIs, databases, and logs.
Automate repetitive data tasks using Python scripting and monitor the health of data pipelines.
Implement data validation checks and document data lineage and technical workflows for scalability.
Strong proficiency in Python programming; familiarity with Pandas or PySpark is a plus.
Advanced SQL skills including Joins, Window Functions, and Query Optimization.
Currently pursuing or recently completed a degree in Computer Science, Information Technology, Data Science, or related quantitative field.
Work Experience Required: Not explicitly mentioned in the JD.
Operates effectively in technical pipeline development and automation with a solid foundation in Python and SQL.
Has familiarity with data engineering fundamentals including REST APIs and data validation techniques.
Likely to have exposure to cloud platforms and big data tools (AWS, GCP, Azure, Apache Spark, Kafka) and be oriented towards troubleshooting and system resilience.