Data Engineer II

Make data foundations practical for AI and workforce analytics as part of Deloitte’s Human Capital practice. This onsite role in Jacksonville, FL focuses on designing and operationalizing modern data architecture and engineering delivery, so clients can turn complex workforce and human capital data into trusted, secure, scalable solutions for AI/ML/GenAI use cases.

What you’ll build and deliver

• Lead the design, development, and delivery of analytics solutions addressing complex workforce and human capital challenges across industries.
• Build and maintain scalable data pipelines, dashboards, and reporting frameworks using SQL and Tableau (or equivalent visualization tools).
• Translate ambiguous business problems into structured analytical approaches, clearly communicating findings and recommendations to technical and non-technical stakeholders.
• Design and deliver intuitive, executive-ready reports and dashboards that make complex workforce data accessible and actionable.
• Design, build, and implement reusable analytics products and assets that meet client needs and extend Human Capital service offerings.
• Support business development activities including proposals, client presentations, and thought leadership content.

AI-enabled data foundations and end-to-end ownership

• Enable AI, ML, and GenAI solutions by supporting data architecture and engineering delivery 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.
• Work with Human Capital product managers and clients to design and deliver data-driven workforce and human capital analytics solutions, owning outcomes from data modeling to stakeholder presentations.
• Collaborate with data science, ML engineering, and product stakeholders in a blended onshore/offshore delivery team to move use cases into production-ready pipelines and platforms with strong data governance, lineage, quality controls, and monitoring.

Required skills

• 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.
• Strong interpersonal skills and professional demeanor.
• Ability to meet deadlines.
• Ability to provide clear guidance to others.
• 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 and 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.
• Must be legally authorized to work in the United States without employer sponsorship.

Technologies you’ll use

• SQL, Tableau, Python, R, Databricks, Snowflake
• RAG, embeddings, vector search

Team focus

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, including an MS or 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 HCM, Salesforce) or in HR data domains.
• Experience operationalizing LLMOps and MLOps capabilities, including evaluation, monitoring, governance workflows, and model/prompt/version management.
• Cloud experience on AWS, Azure, or GCP, 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 (not only one-off deliverables), with ethics and privacy practices, including consent, PII handling, and bias boundary awareness.

Compensation

The estimated wage range for this role is $91,100 to $179,500 per year. You may also be eligible for a discretionary annual incentive program, subject to program rules and based on individual and organizational performance.