Data Engineer II

Deloitte’s Human Capital practice is building data and engineering capabilities that power AI, ML, and GenAI solutions for workforce analytics. In this onsite role in Jacksonville, FL, you will help design and deliver modern data foundations and analytics products, partnering across teams to move from structured requirements to executive-ready outcomes.

You will work on end-to-end delivery for analytics and data engineering, including scalable pipelines, trusted data architecture, and retrieval-focused foundations for LLM-powered applications. The work supports client engagements across industries and includes collaboration within a blended onshore and offshore delivery model.

What you’ll do

• Lead the design, development, and delivery of analytics solutions addressing complex workforce and human capital challenges for clients.
• Build and maintain scalable data pipelines, dashboards, and reporting frameworks using SQL and Tableau (or equivalent visualization platforms).
• Convert ambiguous business problems into structured analytical approaches, communicating findings and recommendations to technical and non-technical stakeholders.
• Collaborate across service lines to embed AI-enabled capabilities and emerging data methodologies into client solutions.
• Design and deliver executive-ready reports and dashboards that make complex workforce data accessible and actionable.
• Design, build, and implement reusable analytics products and assets that extend Deloitte’s Human Capital service offerings.
• Support data architecture and engineering delivery that enables AI, ML, and GenAI solutions with trusted, secure, observable, and scalable data from ingestion through consumption.
• Operationalize modern data and retrieval foundations for LLM-powered applications, including RAG, embeddings, vector search, and governed access to structured and unstructured data.
• Partner directly with Human Capital product managers and clients to deliver data-driven workforce and human capital analytics solutions, owning delivery from data modeling through stakeholder presentations.
• Work as part of a blended onshore/offshore delivery team, aligning with data science, ML engineering, and product stakeholders to productionize pipelines and platforms with strong governance, lineage, data quality controls, and monitoring.
• Contribute to business development through proposals, client presentations, and thought leadership content.

Required qualifications

• 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 environment and meet deadlines.
• Ability to provide clear guidance to others.
• Strong interpersonal skills and professional demeanor.
• Bachelor’s degree in a 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 work, clients, and industries/sectors served.
• Must be legally authorized to work in the United States without employer sponsorship, now or in the future.

Technologies you’ll use

• SQL, Tableau
• Python, R
• Databricks, Snowflake
• Retrieval-augmented generation (RAG), embeddings, vector search

Team context

HC Forward is a dedicated innovation partner accelerating the future of Human Capital by building market-aligned products, platforms, and services that apply AI, data, and engineering to modernize HR experiences and outcomes.

Preferred qualifications

• Advanced degree (Master of Science or Doctor of Philosophy) and/or relevant certifications.
• Client-facing or consulting experience, including exposure to Human Capital platforms and integrations (Workday, SAP SuccessFactors, Oracle HCM, Salesforce) or HR data domains.
• Experience operationalizing LLM Ops and ML Ops capabilities, including evaluation, monitoring, governance workflows, and model/prompt/version management.
• Cloud experience on AWS, Microsoft Azure, or Google Cloud Platform, including managed data platforms and scalable compute patterns.
• Experience explaining complex data and technology concepts, documenting decisions, and collaborating across product, data science/ML, data engineering, platform, and security teams.
• Experience building repeatable analytics product capabilities (tools, models, or platforms) and familiarity with ethics and privacy practices, including consent, PII, and bias boundaries.

Compensation

• Salary range: $91,100 to $179,500 per year.
• May also be eligible for a discretionary annual incentive program, subject to applicable program rules and performance factors.