<p>We are seeking a talented and motivated Python Data Engineer to join our global team. In this role, you will be instrumental in expanding and optimizing our data assets to enhance analytical capabilities across the organization. You will collaborate closely with traders, analysts, researchers, and data scientists to gather requirements and deliver scalable data solutions that support critical business functions.</p><p><br></p><p>Responsibilities</p><ul><li>Develop modular and reusable Python components to connect external data sources with internal systems and databases.</li><li>Work directly with business stakeholders to translate analytical requirements into technical implementations.</li><li>Ensure the integrity and maintainability of the central Python codebase by adhering to existing design standards and best practices.</li><li>Maintain and improve the in-house Python ETL toolkit, contributing to the standardization and consolidation of data engineering workflows.</li><li>Partner with global team members to ensure efficient coordination and delivery.</li><li>Actively participate in internal Python development community and support ongoing business development initiatives with technical expertise.</li></ul>
We are looking for a skilled Data Engineer to join our team in Houston, Texas. As part of the Manufacturing industry, you will play a pivotal role in developing and maintaining data infrastructure critical to our operations. This is a long-term contract position that offers the opportunity to work on innovative projects and collaborate with a dynamic team.<br><br>Responsibilities:<br>• Design and implement scalable data pipelines to support business operations and analytics.<br>• Develop, test, and maintain ETL processes for efficient data extraction, transformation, and loading.<br>• Utilize tools such as Apache Spark and Hadoop to manage and process large datasets.<br>• Integrate and optimize data streaming platforms like Apache Kafka.<br>• Collaborate with cross-functional teams to ensure data solutions align with organizational goals.<br>• Monitor and troubleshoot data systems to ensure optimal performance and reliability.<br>• Create and maintain documentation for data processes and systems.<br>• Stay updated on emerging technologies and recommend improvements to enhance data engineering practices.<br>• Ensure data security and compliance with industry standards and regulations.
We are looking for an experienced Lead Data Engineer to oversee the design, implementation, and management of advanced data infrastructure in Houston, Texas. This role requires expertise in architecting scalable solutions, optimizing data pipelines, and ensuring data quality to support analytics, machine learning, and real-time processing. The ideal candidate will have a deep understanding of Lakehouse architecture and Medallion design principles to deliver robust and governed data solutions.<br><br>Responsibilities:<br>• Develop and implement scalable data pipelines to ingest, process, and store large datasets using tools such as Apache Spark, Hadoop, and Kafka.<br>• Utilize cloud platforms like AWS or Azure to manage data storage and processing, leveraging services such as S3, Lambda, and Azure Data Lake.<br>• Design and operationalize data architecture following Medallion patterns to ensure data usability and quality across Bronze, Silver, and Gold layers.<br>• Build and optimize data models and storage solutions, including Databricks Lakehouses, to support analytical and operational needs.<br>• Automate data workflows using tools like Apache Airflow and Fivetran to streamline integration and improve efficiency.<br>• Lead initiatives to establish best practices in data management, facilitating knowledge sharing and collaboration across technical and business teams.<br>• Collaborate with data scientists to provide infrastructure and tools for complex analytical models, using programming languages like Python or R.<br>• Implement and enforce data governance policies, including encryption, masking, and access controls, within cloud environments.<br>• Monitor and troubleshoot data pipelines for performance issues, applying tuning techniques to enhance throughput and reliability.<br>• Stay updated with emerging technologies in data engineering and advocate for improvements to the organization's data systems.
We are looking for a skilled Data Engineer to design and implement robust technical solutions for enterprise applications. This role involves creating scalable and secure cloud-native systems on Azure, while collaborating closely with stakeholders to meet business requirements. The ideal candidate will possess strong expertise in data architecture and integration strategies, ensuring high engineering standards and seamless orchestration across systems.<br><br>Responsibilities:<br>• Design and maintain comprehensive technical architectures for enterprise applications, ensuring scalability and security.<br>• Develop integration strategies across multiple systems, including manufacturing, field service, and customer portals.<br>• Collaborate with the Principal Architect to define data contracts and establish effective integration patterns.<br>• Partner with teams in Product, AI/ML Engineering, and business units to translate requirements into functional solutions.<br>• Create reference implementations and frameworks to streamline development processes.<br>• Oversee system-level orchestration and elevate engineering standards across projects.<br>• Implement cloud-native solutions on Azure, leveraging modern tools and technologies.<br>• Provide technical guidance and mentorship to engineering teams, fostering best practices.<br>• Continuously monitor and improve system performance, addressing issues proactively.
<p>We are seeking a Data Governance & Data Quality Platform Engineer responsible for the technical administration, integration, and optimization of enterprise data governance and data quality tools such as Atlan and DQ Labs / Monte Carlo. This role ensures these platforms are scalable, secure, integrated across enterprise data ecosystems, and maintained for high availability and performance. The position also supports automation, data quality monitoring, and compliance reporting initiatives across the organization.</p><p><br></p><p>Key Responsibilities</p><p><br></p><p>1. Platform Engineering & Administration</p><ul><li>Configure and maintain Atlan for metadata management, lineage tracking, and governance workflows</li><li>Configure DQ Labs / data quality tools for data profiling, rule creation, and monitoring dashboards</li><li>Manage user roles, authentication, SSO, RBAC, and security settings across governance platforms</li></ul><p>2. Integration & Automation</p><ul><li>Develop and maintain integrations between data sources, databases, data lakes, and BI tools</li><li>Automate metadata ingestion and data quality checks using APIs, Python scripts, or ETL frameworks</li><li>Configure connectors for enterprise data and analytics platforms</li></ul><p>3. Performance, Scalability & Reliability</p><ul><li>Monitor system health and optimize performance across governance and data quality environments</li><li>Apply patches, updates, and troubleshoot technical issues as needed</li><li>Implement logging, alerting, and proactive monitoring across the platform ecosystem</li></ul><p>4. Technical Support & Issue Resolution</p><ul><li>Provide Tier 3 support for platform‑related issues</li><li>Debug integration failures and resolve configuration conflicts</li><li>Collaborate with vendors for advanced troubleshooting, feature requests, and roadmap alignment</li></ul><p>5. Security & Compliance</p><ul><li>Ensure platforms comply with security and data privacy standards (e.g., GDPR, CCPA)</li><li>Implement encryption, access controls, and audit logging</li><li>Support compliance reporting and risk assessments using platform governance features and data quality metrics</li></ul>
<p><br></p><p>Software Platform Engineer will design, build, and maintain a core Data & Machine Learning platform.</p><p><br></p><p>Platform Development: Design and implement new features for our AWS and Databricks-based platform, staying current with industry trends and advancements in AI. Core Component Implementation: Test and integrate central platform components that support our technology stack and serve tenants across the organization. Collaboration: Partner with other engineering teams to identify and deliver platform enhancements that solve specific business problems. Maintain Excellence: Uphold strict security protocols, compliance controls, and architectural principles in all aspects of your work.</p><p><br></p><p><br></p>
<p>As our portfolio of AI-driven solutions continues to expand, we’re looking for an experienced <strong>Machine Learning Engineer</strong> to join our high-impact data science team. This role offers the opportunity to work across trading, operations, and support functions—delivering production-grade machine learning systems that solve real business problems.</p><p>You’ll collaborate with data scientists, software engineers, and commercial stakeholders to design, build, and deploy models that drive decision-making and innovation. From project scoping to model deployment, you’ll have visibility and influence across the full ML lifecycle.</p><p>🔧 Core Responsibilities</p><ul><li>Act as a thought partner to commercial teams, identifying high-value opportunities for AI/ML applications</li><li>Lead the design, development, and deployment of machine learning systems, with a focus on <strong>NLP</strong>, <strong>LLMs</strong>, and <strong>Generative AI</strong></li><li>Prioritize projects based on business impact and evolving market conditions</li><li>Collaborate with cross-functional teams to gather requirements and align solutions with strategic goals</li><li>Integrate ML solutions—including GenAI—into existing platforms to ensure seamless user experiences and scalable adoption</li><li>Participate in code reviews, experiment design, and tooling decisions to maintain high engineering standards</li><li>Share knowledge and mentor colleagues to build machine learning fluency across the organization</li></ul><p><br></p>
<p>As the Software Engineer, you will be responsible for designing and developing automated solutions and system integrations to optimize our business operations. You will be a key player in gathering requirements from non-technical stakeholders, translating them into technical specifications, and ensuring that the delivered solutions meet their needs. You will be responsible for fostering and maintaining strong relationships with stakeholders, ensuring they have confidence in the technology solutions that support their business processes. Your advanced skills in solution design, AWS, and programming languages will be critical to delivering scalable, reliable, and impactful solutions. </p><p><br></p><p><br></p><p>Automation Development: Design, develop, and oversee the maintenance of automation scripts and tools to streamline and optimize business processes.</p><p>Cloud Integration: Architect and manage integrations between various systems and AWS services, ensuring seamless data flow and system interoperability.</p><p>Solution Design: Architect scalable and reliable integration solutions that align with business requirements and technical constraints.</p><p>Testing & Validation: Oversee and participate in the testing of automation and integration solutions to ensure functionality, reliability, and security.</p><p>Documentation: Maintain detailed documentation of automation processes, integration workflows, and system configurations.</p><p>Continuous Improvement: Lead efforts to identify opportunities for process improvements, proposing and implementing innovative automation solutions across the organization.</p><p>Support & Troubleshooting: Provide high-level support for existing automation and integration solutions, troubleshooting issues, and implementing fixes as necessary.</p><p><br></p><p><br></p><p><br></p>
