<p><strong>About the Role: </strong>We’re seeking a <strong>Senior Data Engineer</strong> with deep expertise in <strong>Python</strong> to design and implement scalable data solutions for complex, high-volume environments. This role involves building robust data pipelines, optimizing workflows, and collaborating with analytics teams to deliver actionable insights.</p><p><br></p><p><strong>Key Responsibilities:</strong></p><ul><li>Develop and maintain advanced <strong>Python-based ETL pipelines</strong> for large-scale data processing.</li><li>Integrate data from multiple sources into secure, high-performance data platforms.</li><li>Collaborate with data scientists and business analysts to enable predictive analytics and reporting.</li><li>Implement best practices for data governance, security, and compliance.</li><li>Optimize data workflows for speed, reliability, and scalability.</li></ul><p><br></p>

<p><strong>Qualifications:</strong></p><ul><li>Bachelor’s or Master’s in Computer Science, Data Engineering, or related field.</li><li>5+ years of experience in <strong>data engineering</strong> with a strong focus on <strong>Python</strong>.</li><li>Proficiency in <strong>SQL</strong>, cloud platforms (Azure, AWS, or GCP), and distributed data frameworks (Spark, PySpark).</li><li>Experience with <strong>data modeling</strong>, ETL processes, and API integrations.</li><li>Strong problem-solving skills and ability to work in fast-paced environments.</li></ul><p><strong>Preferred Skills:</strong></p><ul><li>Familiarity with <strong>energy or industrial data sets</strong> (e.g., operational, sensor, or trading data).</li><li>Experience with <strong>data visualization tools</strong> like Power BI or Tableau.</li><li>Knowledge of containerization (Docker) and orchestration (Kubernetes) is a plus.</li></ul>

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