<h3>Job Description</h3>
Must-Have Skills &amp; Experience:
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<ul>\n
<li>Strong hands-on experience as a Data Engineer.</li>
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<li>Strong proficiency in Python.</li>
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<li>Experience building and maintaining large-scale Apache Spark pipelines on AWS.</li>
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<li>Strong knowledge of the modern AWS Data Lake ecosystem, including:</li>
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<li>Amazon S3</li>
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<li>AWS Glue Data Catalog</li>
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<li>Amazon Athena</li>
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<li>Amazon EMR</li>
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<li>Amazon Redshift</li>
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<li>Experience designing and implementing reliable data ingestion, transformation, and validation pipelines at scale.</li>
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<li>Strong understanding of Data Lake architecture and best practices.</li>
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Differentiator / Preferred Experience:
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<ul>\n
<li>Hands-on experience with AWS Lake Formation permission models.</li>
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<li>Experience designing and testing:</li>
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<li>Row-level security</li>
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<li>Column-level filtering</li>
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<li>LF-TBAC (Tag-Based Access Control)</li>
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<li>Experience designing and validating end-to-end Data Lake permission models.</li>
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<li>Strong experience in test design, validation, and troubleshooting for large-scale data platforms and access-control models.</li>
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