We are looking for a Data Scientist to help strengthen turbine reliability and improve operational visibility across a power generation fleet in Houston, Texas. This position combines hands-on data preparation, advanced analytics, and business reporting to turn complex equipment and performance data into practical insights for engineering and leadership teams. The ideal candidate can move comfortably between developing dashboards, analyzing downtime patterns, and creating predictive tools that support maintenance and performance decisions.<br><br>Responsibilities:<br>• Create and enhance dashboard reporting that highlights fleet financial results, equipment availability, and the primary factors affecting cost and performance.<br>• Convert operational and maintenance data into meaningful metrics and recurring reports for engineering teams, business partners, and leadership stakeholders.<br>• Gather, organize, and refine downtime, outage, and maintenance records from multiple operational sources and field documentation to support reliable analysis.<br>• Evaluate failure and outage events to identify root causes and categorize trends across mechanical, electrical, controls, weather, and grid-related issues.<br>• Build and maintain a dependable historical data set that supports querying, trend analysis, and long-term reliability reviews across the turbine fleet.<br>• Design and implement statistical and machine learning models that anticipate downtime risk, detect component deterioration, and support earlier intervention.<br>• Develop anomaly detection and early alert solutions using sensor and operating data such as vibration, temperature, pressure, and combustion-related measurements.<br>• Partner with reliability, operations, engineering, and asset management teams to validate analytical findings, improve data pipelines, and recommend maintenance strategy adjustments based on observed trends.<br>• Present technical conclusions and business implications clearly to both specialized and non-technical audiences, including management and leadership teams.
We are looking for a Data Engineer to join our Data & Analytics team in Houston, Texas, and help strengthen the reporting foundation that supports decisions across the business. In this role, you will shape data into reliable, business-ready models, develop scalable reporting structures, and work closely with teams such as Finance and Operations to turn complex rules into clear insights. This position blends technical data engineering with analytics-focused development, offering the opportunity to improve reporting quality, maintain dependable data flows, and contribute to ongoing enhancements in our analytics environment.<br><br>Responsibilities:<br>• Develop and maintain structured data models, including staging layers, reporting tables, and dimensional designs within the Azure-based data warehouse environment.<br>• Create and support Power BI semantic models, calculated measures, security configurations, dashboards, and reports used for operational and enterprise reporting.<br>• Monitor scheduled data workflows and dataset refresh activity, investigate processing issues, and resolve failures to keep reporting available and accurate.<br>• Adjust and enhance existing ETL and orchestration processes as business needs evolve, using tools such as Azure Data Factory and related Microsoft data platforms.<br>• Collaborate with stakeholders across functions to translate reporting needs, financial logic, and operational rules into dependable analytical solutions.<br>• Produce clear technical and business documentation covering model design, metric definitions, transformation logic, and data ownership.<br>• Apply and help refine development standards for naming, modeling approach, query design, and reporting structure to improve consistency and quality.<br>• Identify opportunities to streamline current data practices, improve performance, and introduce effective tools or methods that strengthen analytics capabilities.
<p>Join a growing data engineering team supporting mission-critical analytics and business operations within the <strong>energy, commodities trading, oil & gas, or financial services sector</strong>. This role is focused on designing and supporting cloud-based data solutions using <strong>Python, Snowflake, and AWS</strong>, enabling scalable, reliable, and high-performance data platforms.</p><p>You will work closely with business stakeholders, analysts, and engineering teams to build production-grade data pipelines, modernize legacy data environments, and deliver trusted datasets that support operational and strategic decision-making.</p><p><br></p><p>Responsibilities</p><ul><li>Design, develop, and maintain scalable <strong>Python-based data pipelines</strong> that ingest, transform, and deliver data from internal and external sources.</li><li>Build and optimize data models within <strong>Snowflake</strong>, ensuring performance, scalability, and cost efficiency.</li><li>Develop ELT/ETL solutions leveraging cloud-native AWS services.</li><li>Create, monitor, and support batch and near real-time data integration workflows.</li><li>Work with structured, semi-structured, and time-series datasets from operational, trading, financial, and market data systems.</li><li>Modernize legacy data processes and migrate legacy database workloads into modern cloud architectures.</li><li>Implement data quality, reconciliation, monitoring, and alerting capabilities across the data platform.</li><li>Collaborate with analysts, traders, business users, and technology teams to deliver data solutions aligned with business objectives.</li><li>Participate in code reviews, testing, documentation, and deployment activities following engineering best practices.</li><li>Support production environments and troubleshoot data pipeline issues as needed.</li></ul><p><br></p><p><br></p><p><br></p>
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 an experienced Senior Data Engineer to help design and enhance scalable data platforms that support critical business operations in Houston, Texas. This role is ideal for someone who enjoys building reliable pipelines, improving data accessibility, and working with modern big data technologies in a service-focused environment. The successful candidate will play a key role in shaping data architecture, enabling analytics, and maintaining high standards for performance, quality, and governance.<br><br>Responsibilities:<br>• Design, build, and optimize large-scale data pipelines that collect, transform, and deliver data from multiple sources.<br>• Develop robust ETL workflows using Python and Spark to support reporting, analytics, and operational data needs.<br>• Implement and maintain data solutions across distributed processing environments, including Hadoop and Azure Databricks.<br>• Create streaming and batch data integrations using Kafka and related technologies to ensure timely and dependable data movement.<br>• Collaborate with analysts, engineers, and business stakeholders to translate requirements into scalable technical solutions.<br>• Monitor pipeline performance, troubleshoot data issues, and apply improvements that increase reliability and efficiency.<br>• Establish data quality controls, validation processes, and documentation to support governance and long-term maintainability.<br>• Contribute to platform enhancements and technical initiatives, including changes to data infrastructure or internal processing frameworks when needed.
<p>Financial Analyst</p><p>The Woodlands, TX (Fully In-Office)</p><p>Our client, a growing regional organization with operations across multiple states, is seeking a Financial Analyst for an immediate opportunity. This is a newly created position driven by company growth and offers significant visibility throughout the organization.</p><p>The Financial Analyst will partner closely with Accounting, Finance, Operational, Supply Chain, and Logistics leadership to analyze business performance, develop meaningful reporting, and identify opportunities for operational improvement. This role is ideal for a data-driven professional who enjoys working with large datasets, building impactful dashboards, and supporting strategic decision-making.</p><p>Key Responsibilities</p><ul><li>Analyze operational and financial data to identify trends, opportunities, and key performance indicators (KPIs).</li><li>Develop, maintain, and enhance complex reporting and dashboards utilizing Power BI.</li><li>Partner with Accounting, Finance, Operations, Supply Chain, and Logistics teams to provide actionable insights that drive business performance.</li><li>Monitor and analyze capital expenditures (CapEx) and operational expenditures (OpEx).</li><li>Support the purchase, movement, tracking, and analysis of physical goods across multiple locations.</li><li>Perform supply chain and logistics analysis to identify inefficiencies, optimize processes, and improve operational performance.</li><li>Analyze inventory movement, utilization trends, transportation metrics, and distribution-related data to support business objectives.</li><li>Assist leadership with forecasting, budgeting, performance analysis, and operational reporting.</li><li>Create and automate reporting processes to improve efficiency and decision-making.</li><li>Present findings and recommendations to various levels of management.</li></ul><p><br></p>
<p>As our portfolio of AI-driven solutions continues to expand, we’re looking for an experienced Machine Learning Engineer 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 NLP, LLMs, and Generative AI</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>Our client, a B2B organization in Houston, is looking for a Digital Marketing Analyst to turn marketing data into clear, actionable insight. This person will measure campaign performance across channels, build reporting that leadership relies on, and help the team spend smarter. It's a great fit for someone who is as comfortable telling the story behind the numbers as building the dashboard.</p><p><br></p><p><strong>Responsibilities</strong></p><ul><li>Build and maintain dashboards and recurring reports in [Tableau / Power BI / Looker Studio]</li><li>Analyze performance across paid, organic, email, social, and web channels to identify trends and opportunities</li><li>Manage GA4 configuration, event tracking, and tag management through Google Tag Manager</li><li>Develop and refine attribution models to measure channel contribution to revenue</li><li>Calculate and report on KPIs including CAC, ROAS, conversion rates, and customer lifetime value</li><li>Partner with marketing, sales, and finance to define goals and measurement frameworks</li><li>Design and analyze A/B and multivariate tests</li><li>Present findings and recommendations tostakeholders in clear, non-technical terms</li></ul><p><br></p><p><br></p>