Results for Data Support Engineer Jobs in Houston, TX

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Data Engineer

Houston, TX
onsite
Temporary to Hire
0 - 0 USD / Yearly
We are looking for a Data Engineer to join a growing team supporting data-driven initiatives within the energy and natural resources sector in Houston, Texas. This contract position with the potential to become permanent is ideal for someone who enjoys building reliable data pipelines, improving data accessibility, and working with modern big data technologies. The role offers the opportunity to contribute to scalable data solutions that support operational and business insights. Responsibilities: • Design, build, and maintain scalable data pipelines to collect, transform, and deliver data from multiple sources • Develop and optimize ETL workflows to support analytics, reporting, and downstream applications • Use Python and Apache Spark to process large-volume datasets efficiently and reliably • Work with Hadoop-based environments to manage distributed data storage and processing needs • Implement and support Kafka-based data streaming solutions for real-time data movement • Partner with technical and business stakeholders to understand data requirements and translate them into practical engineering solutions • Monitor pipeline performance, troubleshoot data issues, and improve overall data quality and reliability
2026-10-21T00:00:00Z

Data Engineer

Houston, TX
onsite
Permanent / Full Time
110000 - 130000 USD / Yearly
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. Responsibilities: • Develop and maintain structured data models, including staging layers, reporting tables, and dimensional designs within the Azure-based data warehouse environment. • Create and support Power BI semantic models, calculated measures, security configurations, dashboards, and reports used for operational and enterprise reporting. • Monitor scheduled data workflows and dataset refresh activity, investigate processing issues, and resolve failures to keep reporting available and accurate. • Adjust and enhance existing ETL and orchestration processes as business needs evolve, using tools such as Azure Data Factory and related Microsoft data platforms. • Collaborate with stakeholders across functions to translate reporting needs, financial logic, and operational rules into dependable analytical solutions. • Produce clear technical and business documentation covering model design, metric definitions, transformation logic, and data ownership. • Apply and help refine development standards for naming, modeling approach, query design, and reporting structure to improve consistency and quality. • Identify opportunities to streamline current data practices, improve performance, and introduce effective tools or methods that strengthen analytics capabilities.
2026-10-05T00:00:00Z

Senior Data Engineer

Houston, TX
onsite
Permanent / Full Time
140000 - 160000 USD / Yearly
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. Responsibilities: • Design, build, and optimize large-scale data pipelines that collect, transform, and deliver data from multiple sources. • Develop robust ETL workflows using Python and Spark to support reporting, analytics, and operational data needs. • Implement and maintain data solutions across distributed processing environments, including Hadoop and Azure Databricks. • Create streaming and batch data integrations using Kafka and related technologies to ensure timely and dependable data movement. • Collaborate with analysts, engineers, and business stakeholders to translate requirements into scalable technical solutions. • Monitor pipeline performance, troubleshoot data issues, and apply improvements that increase reliability and efficiency. • Establish data quality controls, validation processes, and documentation to support governance and long-term maintainability. • Contribute to platform enhancements and technical initiatives, including changes to data infrastructure or internal processing frameworks when needed.
2026-10-01T00:00:00Z

Data Engineer - Lead

Houston, TX
onsite
Permanent / Full Time
175000 - 225000 USD / Yearly
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. Responsibilities: • Develop and implement scalable data pipelines to ingest, process, and store large datasets using tools such as Apache Spark, Hadoop, and Kafka. • Utilize cloud platforms like AWS or Azure to manage data storage and processing, leveraging services such as S3, Lambda, and Azure Data Lake. • Design and operationalize data architecture following Medallion patterns to ensure data usability and quality across Bronze, Silver, and Gold layers. • Build and optimize data models and storage solutions, including Databricks Lakehouses, to support analytical and operational needs. • Automate data workflows using tools like Apache Airflow and Fivetran to streamline integration and improve efficiency. • Lead initiatives to establish best practices in data management, facilitating knowledge sharing and collaboration across technical and business teams. • Collaborate with data scientists to provide infrastructure and tools for complex analytical models, using programming languages like Python or R. • Implement and enforce data governance policies, including encryption, masking, and access controls, within cloud environments. • Monitor and troubleshoot data pipelines for performance issues, applying tuning techniques to enhance throughput and reliability. • Stay updated with emerging technologies in data engineering and advocate for improvements to the organization's data systems.
2026-10-05T00:00:00Z

Data Scientist

Houston, TX
onsite
Permanent / Full Time
140000 - 170000 USD / Yearly
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. Responsibilities: • Create and enhance dashboard reporting that highlights fleet financial results, equipment availability, and the primary factors affecting cost and performance. • Convert operational and maintenance data into meaningful metrics and recurring reports for engineering teams, business partners, and leadership stakeholders. • Gather, organize, and refine downtime, outage, and maintenance records from multiple operational sources and field documentation to support reliable analysis. • Evaluate failure and outage events to identify root causes and categorize trends across mechanical, electrical, controls, weather, and grid-related issues. • Build and maintain a dependable historical data set that supports querying, trend analysis, and long-term reliability reviews across the turbine fleet. • Design and implement statistical and machine learning models that anticipate downtime risk, detect component deterioration, and support earlier intervention. • Develop anomaly detection and early alert solutions using sensor and operating data such as vibration, temperature, pressure, and combustion-related measurements. • 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. • Present technical conclusions and business implications clearly to both specialized and non-technical audiences, including management and leadership teams.
2026-10-05T00:00:00Z

Data Engineer - Python/Snowflake

Houston, TX
onsite
Permanent / Full Time
110000 - 160000 USD / Yearly
Join a growing data engineering team supporting mission-critical analytics and business operations within the energy, commodities trading, oil & gas, or financial services sector. This role is focused on designing and supporting cloud-based data solutions using Python, Snowflake, and AWS, enabling scalable, reliable, and high-performance data platforms.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. Responsibilities<ul><li>Design, develop, and maintain scalable Python-based data pipelines that ingest, transform, and deliver data from internal and external sources.</li><li>Build and optimize data models within Snowflake, 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>
2026-10-05T00:00:00Z

Software Engineer Team Lead

Houston, TX
onsite
Temporary to Hire
0 - 0 USD / Yearly
We are looking for a Software Engineer Team Lead to join a Texas-based organization in the credit services industry and play a key role in building and evolving business-critical applications. This contract-to-permanent opportunity is ideal for a senior technical leader who enjoys staying close to the code while guiding engineering direction, partnering with internal stakeholders, and supporting distributed teams. The position is primarily hands-on, with a strong emphasis on application architecture, modernization, and delivery across a Microsoft and Azure-focused environment. Responsibilities: • Lead technical design and contribute directly to development efforts, dedicating the majority of time to coding, solution architecture, and problem-solving. • Build, enhance, and support web applications using C#, .NET, Angular, SQL Server, and Azure services such as App Services, Functions, monitoring, and messaging components. • Drive modernization initiatives for existing systems while ensuring ongoing reliability, performance, and maintainability of current applications. • Partner with engineering team members across regions to coordinate development efforts, share technical guidance, and maintain delivery quality. • Work closely with business and technology stakeholders across the department to translate needs into scalable software solutions. • Establish and improve CI/CD practices to strengthen release processes, development efficiency, and code quality. • Incorporate AI-assisted development tools and emerging agent-based workflows into engineering practices to improve speed and output quality. • Provide technical leadership through mentorship, design oversight, and hands-on support without focusing primarily on people management or task administration.
2026-10-14T00:00:00Z

7 results for Data Support Engineer in Houston, TX