Data Engineer II

Deloitte • Tampa, FL

10d • $91,100 - $179,500

About The Position

This hands-on, delivery-oriented role designs, builds, and implements reusable analytics products and assets that address client needs and extend Deloitte’s Human Capital service offerings. The Data Engineer Consultant supports data architecture and engineering delivery for AI, machine learning, and generative AI solutions, ensuring data is trusted, secure, observable, and scalable from ingestion through consumption. The role also designs and operationalizes data and retrieval foundations for LLM-powered applications, including RAG, embeddings, vector search, and governed access to structured and unstructured data.

Working directly with Human Capital product managers and clients, the role delivers data-driven workforce and human capital analytics solutions end to end, from data modeling through stakeholder presentations. It builds dashboards, reports, and reusable analytics products that turn complex workforce data into actionable insights. The position is part of a blended onshore/offshore delivery team and partners with data science, ML engineering, and product stakeholders to translate use cases into production-ready pipelines and platforms with governance, lineage, quality controls, and monitoring.

Requirements

• Bachelor’s degree in a STEM field such as computer science, engineering, statistics, or data science.
• At least 2 years of experience in data science, data engineering, or analytics.
• At least 2 years of modern data and AI engineering experience, including data modeling, batch and streaming pipelines, structured and unstructured processing, and feature engineering/serving fundamentals.
• At least 1 year of experience with machine learning concepts, LLM applications, or AI-augmented analytics workflows.
• At least 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, depending on work and clients served.
• Must be legally authorized to work in the United States without employer sponsorship now or in the future.
• Ability to work independently and collaboratively 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, dynamic environment.
• Strong interpersonal skills and professional demeanor.
• Ability to meet deadlines.
• Ability to provide clear guidance to others.

Nice To Haves

• 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 such as Workday, SAP SuccessFactors, Oracle HCM, or Salesforce, or experience in HR data domains.
• Experience operationalizing LLMOps and MLOps capabilities, including evaluation, monitoring, governance workflows, and model, prompt, or version management.
• Experience with AWS, Microsoft Azure, or Google Cloud Platform, 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 developing analytics products, such as repeatable tools, models, or platforms, rather than one-off deliverables.
• Knowledge of ethics and privacy practices, including recognizing consent, PII, and bias boundaries and escalating appropriately.

Responsibilities

• Lead the design, development, and delivery of analytics solutions for 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 platforms.
• Translate ambiguous business problems into structured analytical approaches and communicate 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.
• Support business development through proposals, client presentations, and thought leadership content.
• Design and deliver intuitive, executive-ready reports and dashboards that make complex workforce data accessible and actionable.
• Work with Human Capital product managers and clients to design and deliver end-to-end data-driven workforce and human capital analytics solutions.
• Design and operationalize modern data and retrieval foundations for LLM-powered applications, including RAG, embeddings, vector search, and governed data access.
• Partner with data science, ML engineering, and product stakeholders to develop production-ready pipelines and platforms with governance, lineage, quality controls, and monitoring.

Benefits

• Discretionary annual incentive program, subject to program rules and applicable factors.
• Broad range of employee benefits.
• Professional development opportunities, including on-the-job learning, formal development programs, mentorship, and leadership opportunities.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level