Requisition Id : 4547 Title : Application Developer II (3658-1) Req. Owner : Shrikant Joshi Client : US Steel Work Location City: Pittsburgh Work State : Pennsylvania Expected Start Date : Sep/01/2026 Expected End Date : Sep/01/2027 Description : ·Position: GCP Developer ·Location: Pittsburgh, PA ·Work Arrangement: Remote, but candidate must be local/within reasonable distance and able to come onsite occasionally when required ·Experience:Strong hands-on GCP development experience ·Required Skills: oGoogle Cloud Platform (GCP) oData Pipelines / Data Engineering oBig Data oBigQuery oPython oCloud Run oSQL oGoogle Cloud Storage (GCS) oVertex AI – Required oAI Application development/integration ·Key Focus: Candidate should have strong experience building data pipelines and big-data solutions on GCP, with hands-on Python, BigQuery, SQL, Cloud Run, and GCS experience. ·AI Requirement: Practical experience developing or integrating AI applications using Vertex AI is mandatory. Job Title: GCP Data Engineer – AI Focus Role Overview: Seeking a highly motivated GCP Data Engineer to join our Innovation and Platform Architecture team. The candidate will play a crucial role in building and operating cloud-native data pipelines and AI-enabled applications on Google Cloud Platform, spanning the ingestion, transformation, and retrieval of enterprise data for both analytics and generative AI use cases. The ideal candidate should be proactive, detail-oriented, and capable of collaborating with stakeholders to ensure project success. Key Responsibilities: •Deliver solutions that enable operational and business users to access trusted data and AI-driven insights. •Design, build, and maintain end-to-end data pipelines on Google Cloud Platform, landing data in Google Cloud Storage and modeling it in BigQuery across layered raw, refined, and curated datasets. •Develop and support AI and retrieval-augmented generation solutions using Vertex AI, including embedding generation, vector search, and grounding against enterprise document and structured data sources. •Build and deploy containerized services and APIs on Cloud Run, publishing and versioning images through Artifact Registry. •Orchestrate and schedule pipeline execution using Cloud Workflows and Cloud Scheduler, including monitoring, retry logic, and error handling. •Develop transformation logic and data quality assertions in Dataform or equivalent SQL transformation frameworks. •Follow best practices for governance, security, lifecycle management, and data protection, including least-privilege Cloud IAM design and service account management, ensuring compliance with enterprise standards. •Collaborate with stakeholders to gather requirements and translate them into technical specifications and data models. •Evaluate and recommend tools, technologies, and platforms to enhance productivity and achieve business outcomes. •Stay current with the latest trends and advancements in the cloud data and AI space. •Demonstrate continuous learning and growth while gradually assuming increased ownership and responsibility. Required Qualifications: •2+ years of hands-on experience engineering data solutions on Google Cloud Platform. •Hands-on experience with BigQuery, including SQL development, partitioning and clustering, and cost-aware query design. •Hands-on experience with Vertex AI for building, deploying, or consuming machine learning and generative AI capabilities. •Experience with Google Cloud Storage, including bucket organization, lifecycle policies, and structured data landing patterns. •Working knowledge of Cloud IAM, including roles, service accounts, and least-privilege access design. •Experience deploying and operating containerized services on Cloud Run. •Proficiency in SQL and Python. •Excellent problem-solving and critical-thinking skills. •Strong communication skills with the ability to translate user needs into technical solutions. •Ability to work independently, manage priorities, and operate with high self-sufficiency. •A dedicated work ethic and commitment to delivering high-quality results. Preferred Qualifications (Nice-to-Haves): •Experience with Dataform for managing SQL transformation workflows, dependency graphs, and data quality assertions. •Experience orchestrating and scheduling pipelines with Cloud Workflows and Cloud Scheduler. •Experience managing container images and artifacts in Artifact Registry. •Familiarity with BigQuery Agents and the BigQuery Conversational API, or comparable natural-language-to-data interfaces. •Familiarity with retrieval-augmented generation patterns, including document parsing, chunking strategies, and vector search. •Experience integrating cloud data platforms with enterprise source systems such as ERP, scheduling, or document repositories. •Experience working within Agile/Scrum development methodologies. •Google Cloud Professional Data Engineer or Professional Machine Learning Engineer certification. Work Location: Remote Competencies : N/A No. of Positions : 1 Employment Type : Contractor, W2 or 1099 okay Travel Paid : No Type Of Candidate Needed : Either-Employee Or Sub Influencer : I2