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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer II - **Company:** Deloitte T.T.L. - **Location:** Atlanta, GA, United States - **Salary:** $91,100.0 - $179,500.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Business Analytics Applications, Data Analysis, Microsoft Azure, Cloud Computing, Data Architecture, Information Engineering, Data Governance, Data Infrastructure, Python (Programming Language), Machine Learning, Oracle (Applications), SuccessFactors, Salesforce.Com, Search Technologies, SQL Databases, Tableau (Software), Unstructured Data, Data Processing, Google Cloud, Feature Engineering, Large Language Models, Snowflake, Generative AI, Information Technology, Data Analytics, Data Management, Machine Learning Operations, Tools for Reporting, Claude, Google Gemini, GPT, Software Version Control, Data Pipelines, Workday, Databricks - **Published:** October 17, 2026 - **Apply:** https://dejobs.org/x/x/B9ADA592D2B94E6591FF3DA943445319/job/ ## About the Role * Ability to work independently and collaborate as part of a team * Effective written and verbal communication skills * Meticulous attention to detail and quality of work product * Ability to build and sustain professional relationships * Ability to lead projects or workstreams * Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment * Strong interpersonal skills and professional demeanor * Ability to meet deadlines * Ability to provide clear guidance to others, Required: * Bachelor's degree in a Science, Technology, Engineering, and Mathematics (STEM) field (e.g., Computer Science, Engineering, Statistics, Data Science) * 2+ years of experience in data science, data engineering, or analytics. * 2+ years of modern data & AI engineering, including data modeling, batch/streaming pipelines, structured/unstructured processing, and feature engineering/serving fundamentals. * 1+ years of experience with machine learning concepts, large language model applications, or AI-augmented analytics workflows. * 2+ years of experience using Python or R for statistical modeling and data wrangling, including proficiency in Databricks or Snowflake. * Ability to travel 0-25%, on average, based on the work you do and the clients and industries/sectors you serve. * Must be legally authorized to work in the United States without the need for employer sponsorship, now or at any time in the future. Preferred: * Advanced degree, including a Master of Science (MS) or Doctor of Philosophy (PhD), and/or relevant certifications. * Direct experience in client-facing or consulting environments, with Human Capital platforms and integrations (e.g., Workday, SAP SuccessFactors, Oracle Human Capital Management (HCM), Salesforce), or in Human Resources (HR) data domains. * Experience operationalizing large language model operations (LLMOps) and machine learning operations (MLOps) capabilities, including evaluation, monitoring, governance workflows, and model/prompt/version management. * Cloud experience on one or more of Amazon Web Services (AWS), Microsoft Azure, or Google Cloud Platform (GCP), including managed data platforms and scalable compute patterns. * Experience explaining complex data and technology concepts, articulating risks and trade-offs, documenting decisions, and collaborating across product, data science/ML, data engineering, platform, and security teams. * Experience in analytics product development-building repeatable tools, models, or platforms rather than one-off deliverables-and ethics and privacy practices, including recognizing consent, personally identifiable information (PII), and bias boundaries and escalating appropriately. ## Description Our Human Capital practice is at the forefront of transforming the nature of work. As converging forces reshape industries, our team uniquely addresses the complexities of work, workforce, and workplace dynamics. We leverage sector-specific insights and cross-domain perspectives to help organizations tackle their most challenging workforce issues and align talent strategies with their strategic visions. Our practice is renowned for making work better for humans and humans better at work. Be part of this exciting era of change and join us on this transformative journey. This role is hands-on and delivery-oriented: you will design, build, and implement reusable analytics products and assets that meet client needs and extend our Human Capital service offerings., The Data Engineer Consultant will support data architecture and engineering delivery that enables artificial intelligence (AI), machine learning (ML), and generative AI (GenAI) solutions, ensuring data is trusted, secure, observable, and scalable from ingestion through consumption. You will design and operationalize modern data and retrieval foundations to support large language model (LLM)-powered applications (e.g., Claude, GPT/Codex, Gemini) including patterns such as retrieval-augmented generation (RAG), embeddings, vector search, and governed access to structured and unstructured data and work directly with Human Capital product managers and clients to design and deliver data-driven workforce and human capital analytics solutions, owning end-to-end solutions from data modeling to stakeholder presentations. You will build dashboards, reports, and reusable analytics products, turning complex human capital data into clear, actionable insights. You will be part of a blended onshore/offshore delivery team, partnering with data science, ML engineering, and product stakeholders to translate use cases into production-ready pipelines and platforms with strong data governance, lineage, quality controls, and monitoring. * Lead the design, development, and delivery of analytics solutions that address complex workforce and human capital challenges for clients across industries. * Build and maintain scalable data pipelines, dashboards, and reporting frameworks using Structured Query Language (SQL) and Tableau (or equivalent visualization platforms). * Translate ambiguous business problems into structured analytical approaches, communicating findings and recommendations clearly to both technical and non-technical stakeholders. * Collaborate across service lines to embed AI-enabled capabilities and emerging data methodologies into client solutions. * Support business development efforts including proposals, client presentations, and thought leadership content. * Design and deliver intuitive, executive-ready reports and dashboards that make complex workforce data accessible and actionable.