Senior Data Engineer (ML & AI Focus)

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    "description": "<p><span style=\"font-weight: bold\">About Us</span><br>Greenland Commodities is a science and technology-driven trading house based in Prague, operating across European energy markets. We combine deep market expertise with strong engineering and data capabilities to build real-time, production-grade analytics systems that directly support trading decisions.<br>Our engineering team works closely with traders and analysts to transform complex data into reliable, scalable, and actionable insights.</p>\n<p><br><span style=\"font-weight: bold\">Position Overview</span><br>We are looking for a Senior Data Engineer with strong Data Science and Machine Learning exposure to join our team.<br>This role sits at the intersection of data engineering and applied data science. You will design and build robust data pipelines while also contributing to ML-driven analytics and decision-support systems.<br>The focus is not on pure quantitative finance modeling, but rather on building production-ready data and ML systems that operate reliably in real-time environments.</p>\n<p><br><span style=\"font-weight: bold\">Key Responsibilities</span></p>\n<ul>\n<li>Data Platform Development\n<ul style=\"list-style-type: circle;\">\n<li>Design, build, and maintain scalable data pipelines and architectures for large-scale structured and unstructured data.</li>\n</ul>\n</li>\n<li>ML &amp; Analytics Integration</li>\n</ul>\n<ul>\n<li style=\"list-style-type: none;\">\n<ul style=\"list-style-type: circle;\">\n<li>Work closely with data scientists to deploy and operationalize machine learning models into production systems.</li>\n</ul>\n</li>\n</ul>\n<ul>\n<li>Data Processing &amp; Performance</li>\n</ul>\n<ul>\n<li style=\"list-style-type: none;\">\n<ul style=\"list-style-type: circle;\">\n<li>Optimize data storage and querying performance (high-frequency, large-volume datasets).</li>\n</ul>\n</li>\n</ul>\n<ul>\n<li>Data Quality &amp; Reliability</li>\n</ul>\n<ul>\n<li style=\"list-style-type: none;\">\n<ul style=\"list-style-type: circle;\">\n<li>Implement validation, monitoring, and alerting systems to ensure high data quality and system reliability.</li>\n</ul>\n</li>\n</ul>\n<ul>\n<li>End-to-End Ownership</li>\n</ul>\n<ul>\n<li style=\"list-style-type: none;\">\n<ul style=\"list-style-type: circle;\">\n<li>Own the full lifecycle: data ingestion → transformation → model integration → production deployment.</li>\n</ul>\n</li>\n</ul>\n<ul>\n<li>Cross-Team Collaboration</li>\n</ul>\n<ul>\n<li style=\"list-style-type: none;\">\n<ul style=\"list-style-type: circle;\">\n<li>Collaborate with traders, analysts, and engineers to translate business needs into scalable data solutions.</li>\n</ul>\n</li>\n</ul>\n<ul>\n<li>Process Automation</li>\n</ul>\n<ul>\n<li style=\"list-style-type: none;\">\n<ul style=\"list-style-type: circle;\">\n<li>Automate repetitive workflows and build standardized pipelines for analytics and reporting.</li>\n</ul>\n</li>\n</ul>\n<p><br></p>\n<p><span style=\"font-weight: bold\">Qualifications</span></p>\n<ul>\n<li>Experience\n<ul>\n<li>3+ years in Data Engineering, Backend Engineering, or similar roles</li>\n<li>Experience working with data-driven systems in production environments</li>\n</ul>\n</li>\n<li>Programming\n<ul>\n<li>Strong Python skills (data processing + ML integration)</li>\n<li>Solid SQL knowledge (performance optimization is important)</li>\n</ul>\n</li>\n<li>Data Engineering\n<ul>\n<li>Experience with ETL/ELT pipelines, workflow orchestration, and data modeling</li>\n<li>Familiarity with distributed or large-scale data systems</li>\n</ul>\n</li>\n<li>Databases\n<ul>\n<li>Experience with systems like Vertica, PostgreSQL, or similar analytical databases</li>\n</ul>\n</li>\n<li>Machine Learning / Data Science (Important but Practical)\n<ul>\n<li>Understanding of ML workflows (training, validation, deployment)</li>\n<li>Experience working with time-series or predictive models is a plus</li>\n<li>Focus on application and integration, not theoretical research</li>\n</ul>\n</li>\n<li>Cloud &amp; Infrastructure\n<ul>\n<li>Experience with AWS or similar cloud platforms</li>\n<li>Understanding of cost-efficient and scalable system design</li>\n</ul>\n</li>\n<li>Mindset\n<ul>\n<li>Strong problem-solving skills</li>\n<li>Product-oriented thinking (building systems that are actually used)</li>\n<li>Ability to work in fast-paced environments</li>\n</ul>\n</li>\n</ul>\n<p><br></p>\n<p><span style=\"font-weight: bold\">Nice to Have (Not Required)</span></p>\n<ul>\n<li>Experience in energy markets or commodity trading</li>\n<li>Experience with real-time data systems</li>\n<li>Familiarity with BI tools (Power BI, Tableau)</li>\n<li>Exposure to advanced ML techniques (feature engineering, model evaluation, etc.)</li>\n</ul>\n<p><br></p>\n<p><span style=\"font-weight: bold\">What We Offer</span></p>\n<ul>\n<li>Competitive salary and benefits package</li>\n<li>A fast-paced, engineering-driven environment</li>\n<li>Direct impact on real trading systems</li>\n<li>Collaboration with traders, data scientists, and engineers</li>\n<li>4 weeks vacation + 1 extra week</li>\n<li>3 sick days + 1 birthday leave</li>\n<li>Meal support &amp; public transport contribution</li>\n<li>Modern office in central Prague</li>\n</ul>\n<p><br></p>\n<p><span style=\"font-weight: bold\">Summary (Internal Positioning)</span><br>This is not a pure quant role and not a pure data engineer role.<br>It is ideal for someone who:</p>\n<ul>\n<li>Can build strong data pipelines</li>\n<li>Understands ML systems in practice</li>\n<li>Wants to work on real-time, production trading data</li>\n<li>Prefers impact over theory</li>\n</ul>\n<p> </p>",
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