Data Engineer (Spring, TX, US, 77389)

About us For well over a century, ExxonMobil has been at the heart of creating and growing a modern world. We embrace the power and promise of technology, pushing the boundaries of what's possible. For billions around the world, lives are better and last longer because of the innovative problem solving and reliable energy we provide. And when it comes to developing industrial solutions to reduce carbon emissions, ExxonMobil is truly the leader. We don't stop at "good enough." We are committed to doing what's right, even if it's difficult or unpopular. We hold ourselves to high standards, challenge what's possible and invest in innovation to meet society's critical needs. Real change begins with bold questions, drive, and ambition. Here, your talent, determination and contributions shape how far you'll go and the impact you'll make along the way. Our future success depends on exceptional people. We invest in developing talent through meaningful work, challenging assignments, mentorship, and experiences that help build the next generation of leaders. Our Culture We are uniquely ExxonMobil. Integrity, care, excellence, resilience and courage, these core values determine how we work every day. At ExxonMobil, our values aren't just words— they're how we show up, focused on delivering the right answer, the right way, every day. What role you will play on our team As part of the Low Carbon Solutions (LCS) IT team, help build scalable data pipelines and build out the physical data platform as a key foundation to support multiple Low Carbon Solution (LCS) business use cases. Design and implement modern, cloud-based data solutions working closely across the LCS IT team and aligned to LCS business & IT architectures. Collaborate with various IT and business teams to deliver high-quality datasets & data products aligned with stakeholder needs. What you will do Leads and participates in gathering complex and often unique business requirements by defining the business problem and data requirements Design, build, and maintain robust batch and / or real-time data pipelines for ingesting, processing, and transforming large-scale datasets. Assist with logical data model development, and update where applicable (nice to have) Develop, maintain, document and optimize physical data models & data flow diagrams to support transactional solutions, analytics, reporting, and business workflows. Integrate APIs/modern integrations and data sources, ensuring reliable, monitored and efficient data movement across systems. Work with cross-functional teams to profile data sources, structure, clean, and deliver data for consumers (i.e. applications, visualization tools, end users, etc.) Ensure adherence to data classification and security access through appropriate storage, data management and query optimization for efficient data access. Build enterprise-ready data solutions with strong data governance, quality, and reliability standards. Stay up-to-date with the latest technologies and trends in data engineering and apply them to improve existing data pipelines Integrates standards for platforms and frameworks for source code management, work item and project tracking, DevOps and enterprise architecture Mentor Data Engineers – Associate, providing guidance and support in their professional development and with contractors to follow ExxonMobil standards and architectures About you Skills and Qualifications Bachelor’s degree in computer science, engineering, or related discipline, equivalent practical experience delivering data solutions will also be considered. 7+ years of professional experience in data engineering, data platform development, or related areas. Strong proficiency in Python and SQL for data processing and pipeline development. Hands-on experience building and maintaining scalable data pipelines (batch and streaming). Advanced knowledge of data modeling, ETL/ELT design patterns, and data architecture best practices. Experience with cloud data platforms and distributed data processing frameworks. Hands-on experience with relational and/or NoSQL database technologies. Experience implementing data quality, validation, and monitoring frameworks. Hands-on experience building and maintaining CI/CD pipelines for data workflows. Preferred Qualifications Experience with Azure data services (e.g., Azure Data Factory, Synapse, Databricks). Experience with Snowflake or other equivalent data warehouse or data platforms Strong SQL expertise, including performance tuning and security model implementation. Experience with big data technologies such as Spark or Kafka. Familiarity with data orchestration tools (e.g., Airflow). Experience integrating observability and monitoring into data pipelines. Knowledge of data governance, lineage, and metadata management tools. Prior experience working with Python-based data processing or optimization workflows. Experience with Palantir Foundry, Ontologies, or similar enterprise data platforms Strong p