Data Engineer

POSITION OVERVIEW The Data Engineer is responsible for designing, building, and maintaining the organization's enterprise data pipelines, curated datasets, and analytics platform foundation. This role enables timely, accurate, and trusted decision-making by ensuring reliable, scalable, and governed data flows across the Enterprise Resource Planning (ERP) system, Product Lifecycle Management (PLM) system, and other integrated business applications. The Data Engineer will engineer ingestion and curation from vendor-hosted enterprise data repositories and integration services, including Infor OS Data Lake and supported extraction methods (e.g., Data Fabric Objects API, Compass SQL API / Compass JDBC Driver, ION Data Lake Flows, and ETL Client for Data Lake). The role will enable enterprise analytics and reporting through Microsoft Fabric and Power BI, and will use Spark/PySpark, SQL, and Python to deliver performant, scalable transformations. This role also supports the organization's increasing use of AI-enabled analytics by preparing high-quality, well-governed datasets and following company requirements for responsible and compliant AI usage. KEY JOB RESPONSIBILITIES Data Engineering & Architecture (Microsoft Fabric / Lakehouse) Design and maintain a modern enterprise analytics foundation using Microsoft Fabric (Lakehouse/Warehouse patterns) to support governed reporting and self-service analytics. Build and manage curated data layers aligned to medallion-style processing (raw → standardized → curated) using Spark/PySpark, SQL, and Python. Develop and maintain enterprise data models optimized for analytics performance, consistent KPI definitions, and reuse across business domains. Data Integration & Ingestion (Infor OS Data Lake + APIs + Flows) Develop and support automated ingestion from Infor OS Data Lake using supported extraction/integration methods such as: Data Fabric Objects API (object/file extraction) Compass SQL API / Compass JDBC Driver (query-based extraction) ION Data Lake Flows (scheduled push to connection points) ETL Client for Data Lake (scheduled transfer patterns) Stream Pipelines where applicable for continuous/near real-time delivery Implement incremental loading patterns, orchestration, monitoring, alerting, and failure recovery to ensure reliable delivery of daily/near real-time datasets. Partner with application and integration teams to align ingestion with upstream interfaces, data contracts, and security requirements. Reporting & Analytics Enablement (Power BI + Dataset Modeling) Provide trusted, well-documented datasets that enable enterprise dashboards and self-service analytics in Power BI. Build and maintain business-friendly semantic/dimensional models that support high-performance dashboards and consistent KPI definitions. Support modernization and migration of reporting assets into Microsoft Fabric, ensuring datasets and models align to reporting needs and enterprise metric definitions. Data Quality, Governance & Master Data Support Implement validation, reconciliation, and anomaly detection to ensure accuracy and completeness of curated datasets. Establish automated checks for common data issues (duplicates, missing attributes, invalid statuses, inconsistent units of measure). Partner with master data stakeholders and business data stewards to define standards, drive adoption, and remediate root-cause issues impacting data quality. AI-Enabled Analytics Support (Practical AI Competency) Prepare AI-ready datasets by ensuring data completeness, consistency, lineage, and documentation (e.g., feature-ready curated tables, standardized definitions, and auditability). Support AI-assisted development workflows (e.g., using copilots/assistants to accelerate transformation code generation, documentation, and standardization) while adhering to company AI requirements for accuracy, confidentiality, compliance, and labeling of AI-generated content where required. Operational Excellence (Reliability, Supportability, Documentation) Develop and maintain runbooks, operational documentation, lineage notes, and standardized naming conventions for pipelines, datasets, and reporting layers. Track pipeline health metrics (freshness, completeness, latency, failure rates) and continuously improve reliability and performance. Provide knowledge transfer and training to analysts and IT Business Applications team members to improve overall data fluency. All other duties as assigned by TAS. JOB SKILLS Strong understanding of modern data architectures (data lake/lakehouse/warehouse), data modeling, and ETL/ELT engineering patterns. Proficiency in SQL and Python for data transformation and pipeline development. Hands-on experience with Spark/PySpark for scalable transformations and performance tuning. Experience integrating and extracting data from Infor OS Data Lake using Data Fabric Objects API, Compass SQL API/JDBC, ION Data Lake Flows, ETL Client for Data Lake, and/or Stream Pipelines. Experience developing enterprise analytics assets using Microsoft Fabric and enabling dashboards and self-service reporting using Power BI. Ability to implement data quality controls, reconciliation, documentation, and lineage practices that support trust and auditability. Practical AI competency: ability to prepare AI-ready datasets and responsibly use AI assistants to improve productivity while maintaining accuracy, confidentiality, and compliance. Strong communication skills to translate business needs into technical solutions and collaborate with both technical and non-technical stakeholders. EDUCATION & TRAINING Bachelor's degree in Information Systems, Computer Science, Data Engineering, or a related field; equivalent experience may be considered in lieu of a degree. Preferred training/certifications in one or more areas: cloud data platforms, data engineering, analytics engineering, data governance, or AI fundamentals for data/analytics professionals. MINIMUM REQUIREMENTS 3+ years of experience in data engineering, analytics engineering, or a related technical role. Demonstrated experience building and maintaining curated datasets used for enterprise reporting and analytics. Demonstrated experience with at least two of the following toolsets: Microsoft Fabric (Lakehouse/Warehouse, pipelines/notebooks) Power BI (dataset modeling and dashboard enablement) Infor OS Data Lake extraction/integration methods (Objects API, Compass SQL API/JDBC, ION Data Lake Flows, ETL Client, Stream Pipelines) Spark/PySpark Experience implementing monitoring/alerting or operational runbooks for production data pipelines. Familiarity with manufacturing/operations reporting domains (production, inventory, procurement, costing, project execution) preferred. PHYSICAL REQUIREMENTS/WORK ENVIRONMENT: Position is at least 80% to 95% at a desk working with computer. Ability to exert up to 10 pounds of force occasionally and/or a negligible amount of force frequently or constantly to lift, carry, push, pull or otherwise move objects, including the human body. Performs other physical activities including use of fingers, sitting, stooping, bending, crouching, talking, hearing, and performing repetitive motions. Visual acuity requirements include color, depth perception and field of vision necessary to prepare and analyze data and figures, operate a computer terminal, and conduct extensive reading. The incumbent will be subject to inside environmental conditions. COMPANY OVERVIEW: Join a team driven to excel in all that we do! When you join TAS, you join a Houston-headquartered company that is part of a large Houston-headquartered publicly traded company, Comfort Systems USA, with a solid reputation built on outstanding value, integrity, and customer focus. We offer our customers and employees the best of both worlds: a small company feel with the resources, talent, process, and international reach of a large company. TAS delivers innovative packaged modular systems that are engineered and manufactured in one of our Houston, TX facilities and utilized in data centers, power, and commercial/industrial utility system applications. TAS has successfully delivered and commissioned over 520 packages to over 33 countries. The company is headquartered in Houston, TX and has five ISO 9001 certified manufacturing facilities in Houston, encompassing 1.2m sq. feet with proximity to major shipping ports and interstate highways. TAS manages all logistics and transportation facilitating accelerated construction at customer's facilities. TAS' fastest growing business is the data center market. By applying deep expertise in cooling, thermodynamics, and power, TAS has developed an entire product line that revolutionizes data center delivery. With our tremendous market potential, advanced technological systems, entrepreneurial culture as well as a talented and productive workforce, we continue to set and exceed aggressive market penetration and financial goals. More information is available on the company website at: IMPORTANT NOTICE: TAS has a tobacco-free workplace policy, under which individuals are not allowed to smoke or use tobacco or nicotine products on the TAS premises, while conducting TAS business off premises or take "smoking" breaks during working hours. "smoking" and "tobacco or nicotine products" includes, but is not limited to, product such as cigarettes, e-cigarettes, cigars, pipes, vaping, all forms of smokeless tobacco (chewing tobacco, snuff, dip) and clove cigarettes The above declarations are not intended to be an all-inclusive list of the duties and responsibilities of the job described, nor are they intended to be such a listing of the skills and abilities required to do the job. Rather, they are intended only to describe the general nature of the job. Applications and resumes will be kept on file for a limited time and the Company is under no duty or obligation to contact applicants if they are not selected for the job applied for or if other jobs become available in the future. Applicants that desire to apply for a job that becomes available at the Company in the future, should submit a new employment application or resume. TAS Energy Inc. guarantees equal employment opportunities to all qualified applicants. All qualified applicants will receive consideration for employment, without regard to age, race, color, religion, sex, sexual orientation, gender identity, or national origin.

Created: 2026-03-04