Data Engineer-Adobe Exp Platform

Why GMF Technology?Innovation isn’t just a talking point at GM Financial, it’s how we operate. From generative AI and cloud-native technologies to peer-led learning and hackathons, our tech teams are building real solutions that make a difference. We’re committed to AI-powered transformation, using advanced machine learning and automation to help us reimagine customer interactions and modernize operations, positioning GM Financial as a leader in digital innovation within a dynamic industry.Join us and discover a workplace where your ideas matter, your development is prioritized, and you can truly make a global impact.We are unable to provide visa sponsorship either now or in the future for this position. This position will be posted until filled.What makes You an ideal candidate?Experience with Adobe solutions (ideally Adobe Experience Platform, XDM, RTCDP DTM/Launch) and REST APIsDigital technology solutions (DMPs, CDPs, Tag Management Platforms, Cross-Device Tracking, SDKs, etc.) Knowledge of Real Time-CDP and Journey Analytics solutionSQL experience: querying data and sharing what insights can be derivedWorking knowledge of Agile development /SAFe, Scrum and Application Lifecycle Management.Experience with ingesting various source data formats such as JSON, Parquet, SequenceFile, Cloud Databases, MQ, Relational Databases such as Oracle.Experience with Cloud technologies (such as Azure, AWS, GCP) and native toolsets.Understanding of cloud computing technologies, business drivers and emerging computing trends.Thorough understanding of Hybrid Cloud Computing: virtualization technologies, Infrastructure as a Service, Platform as a Service and Software as a Service Cloud delivery models and the current competitive landscape.Working knowledge of Object Storage technologies to include but not limited to Data Lake Storage Gen2, S3, Minio, Ceph, ADLS etc.Strong background with source control management systems; Build Systems (Maven, Gradle, Webpack); Code Quality (Sonar); Artifact Repository Managers (Artifactory), Continuous Integration/ Continuous Deployment (Azure DevOps).Experience with processing large data sets using Hadoop, HDFS, Spark, Kafka, Flume or similar distributed systems.Experience with NoSQL data stores such as CosmosDB, MongoDB, Cassandra, Redis, Riak or other technologies that embed NoSQL with search such as MarkLogic or Lily Enterprise.Creating and maintaining ETL processesKnowledgeable of best practices in information technology governance and privacy complianceTroubleshoot complex problems and work across teams to meet commitments.Excellent computer skills and proficiency in digital data collection.Ability to work in an Agile/Scrum team environmentStrong interpersonal, verbal, and writing skills.Understanding of big data platforms and architectures, data stream processing pipeline/platform, data lake and data lake housesUnderstanding of cloud solutions such as Google Cloud Platform, Microsoft Azure & Amazon AWS cloud architecture & servicesUnderstanding of GDPR, privacy & security topicsStrong in the use of Microsoft Office software, data querying platforms (Databricks is a plus) and statistical programming tools such as PythonEducation & Work ExperienceHigh School Diploma or equivalent requiredBachelor’s Degree in related field or equivalent experience required2-4 years of hands-on experience with data engineering requiredAdditional Knowledge and SkillsWorking effectively within an AI enabled environment: Ability to use AI tools (e.g., Microsoft Copilot) to support daily workSkills in evaluating AI outputs for accuracy, compliance, and biasExperience integrating AI into workflows to improve efficiency or insightsFamiliarity with AI assisted research, summarization, and content generationUnderstanding of responsible AI use, including ethics and data protectionAI Skills Preferred:Experience with AI assisted software development or automationKnowledge of prompting techniques to improve output qualityAwareness of emerging GenAI capabilities and limitationsWhat We Offer: Generous benefits package available on day one to include: 401K matching, bonding leave for new parents (12 weeks, 100% paid), tuition assistance, training, GM employee auto discount, community service pay and nine company holidays.Our Culture: Our team members define and shape our culture — an environment that welcomes innovative ideas, fosters integrity, and creates a sense of community and belonging. Here we do more than work — we thrive.Compensation: Competitive pay and bonus eligibility.Work Life Balance: Flexible hybrid work environment, 2-days a week in our Las Colinas/Irving, TX office.NOTE: We are unable to consider candidates who require visa sponsorship for this positionThis position is not open to agency submissions#LI-Hybrid#LI-MH1#GmfJobs#GMFJobs #LI-Hybrid #LI-MH1About the roleWe are expanding our efforts into complimentary data technologies for decision support in areas of ingesting and processing large data sets including data commonly referred to as semi-structured or unstructured data. Our interests are in enabling data science and search-based applications on large and low latent data sets in both a batch and streaming context for processing. To that end, this role will engage with team counterparts in exploring and deploying technologies for creating data sets using a combination of batch and streaming transformation processes. These data sets support both off-line and in-line machine learning training and model execution. Other data sets support search engine-based analytics. Exploration and deployment of technologies activities include identifying opportunities that impact business strategy, collaborating on the selection of data solutions software, and contributing to the identification of hardware requirements based on business requirements. Responsibility also includes coding, testing, and documentation of new or modified scalable analytic data systems including automation for deployment and monitoring. This role participates along with team counterparts to develop solutions in an end-to-end framework on a group of core data technologies.In this role you will:Contribute to the evaluation, research, experimentation efforts with batch and streaming data engineering technologies in a lab to keep pace with industry innovationWork with data engineering related groups to inform on and showcase capabilities of emerging technologies and to enable the adoption of these new technologies and associated techniquesContribute to the definition and refinement of processes and procedures for the data engineering practiceWork closely with data scientists, data architects, ETL developers, other IT counterparts, and business partners to identify, capture, collect and format data from the external sources, internal systems, and the data warehouse to extract features of interestCode, test, deploy, monitor, document and troubleshoot data engineering processing and associated automationFull timePosting Date: 2026-06-24