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About This Role
Count on us. Our "we-care" culture is more than just a motto; it's a promise. From day one, we prioritize your growth, well-being, and success. You can count on us to support your career journey and help you achieve your professional goals. Join us.
About the Role
Plante Moran is building the next generation of its data and analytics platform, and we’re looking for an AI‑Native Data Engineer who is excited to build, experiment, and learn fast. You’ll work in a modern Microsoft‑centric ecosystem built on Microsoft Fabric, Azure, and Power BI, designing scalable, governed solutions aligned to Medallion Architecture - with AI treated as part of the data engineering lifecycle. This role is ideal for a go‑getter: someone who takes initiative, loves problem‑solving, is hungry to learn, and has a strong desire to build and create new things.
Your role.
- Build and operate automated, repeatable data pipelines in Microsoft Fabric and Azure (e.g., Data Factory) with strong observability.
- Implement Medallion Architecture (Bronze/Silver/Gold): land raw data, transform/validate/enrich, and publish trusted data products for analytics and AI.
- Ingest data from APIs and enterprise systems into lakehouses and Azure SQL–based stores; model data to support reuse and AI/ML feature needs.
- Develop transformations using Python/PySpark/Spark and SQL/T‑SQL.
- Experience building AI agentic workloads (e.g., Microsoft Copilot Agents, workflow automation, PR review bots, orchestration assistants), or strong interest in learning agent‑based patterns.
- Use Git and CI/CD (e.g., GitHub/GitHub Actions) for source control, reviews, and deployments; leverage Copilot/AI tools to accelerate delivery and documentation.
- Partner with architects and stakeholders to translate ambiguous requirements into scalable, governed solutions.
The Qualifications.
- Bachelor's degree in Computer Science, Information Systems, or related field required.
- 2–4 years in data engineering, analytics engineering, or software development.
- Strong SQL plus Python for data transformation and pipeline logic; experience with PySpark/Spark.
- Hands‑on with Microsoft Fabric (Lakehouse/Data Engineering/Pipelines) and Azure Data Factory; general Azure exposure (Azure SQL, Storage, APIs).
- Experience with Databricks (Azure Databricks preferred).
- Working knowledge of Git and CI/CD basics (branching, PRs, automated checks/deployments).
- Must be able to remain in a stationary sitting position for at least 75% of the time.
- Must be able to lift at least 15 lbs– specific job duties may require additional lifting to move, transport, position and install equipment.
- Frequently positions self to bend and lift packages.
- Occasional moving & lifting of equipment; bending, lifting, climbing required to position self to maintain computers during engagements.
- Person in position needs to occasionally move about the inside of the office to access machinery, cabinets, etc.
- Person in position frequently communicates with individuals who have inquires. Must be able to exchange information in these situations.
- Ability to work in a high stress environment.
- Reliable transportation and valid driver’s license are required including a clean driving record.
- Minimum levels of auto insurance coverage are required.
- Ability to travel locally, work overtime and weekends is required.
Nice to Have’s.
- Experience building AI agentic workloads (e.g., Microsoft Copilot Agents, workflow automation, PR review bots, orchestration assistants), or strong interest in learning agent‑based patterns.
- Familiarity with lakehouse or data warehouse architectures and governance concepts (cataloging/lineage/security).
- Power BI experience with semantic models or tabular modeling.
- PowerShell scripting or automation for deployments and operational workflows.
This is an exempt position, so you may have to work hours that exceed the standard 40-hour work week.
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What makes us different?
On the surface, we’re one of the nation’s largest audit, tax, consulting, and wealth management firms. But dig a little deeper, and you’ll see what makes us different: we’re a relatively jerk-free firm (hey, nobody ‘s perfect) with a world-class culture, consistent recognition as one of Fortune Magazine’s “100 Best Companies to Work For,” and an endless array of opportunities. At Plante Moran, diversity, equity and inclusion means that all staff members have equitable and fair opportunities to succeed, in an inclusive environment, with their individual, unique identities. So, what are you waiting for? Apply now.
Plante Moran enjoys a “Workplace for Your Day” model which, simply put, means we strive for flexibility and balance while staying true to our principally in-person model. We believe that face-to-face interactions are paramount for individual and collective development, but also encourage individuals to work with their supervisor and team to determine their optimal working environment each day.
Plante Moran is committed to a diverse workplace. We strive to create a culture where each person feels accepted and valued. We believe that each person’s ultimate potential begins with first acknowledging their inherent dignity. When we can recognize — and celebrate — our many human differences, we’re able to create a workplace where all staff feel a sense of belonging and an opportunity to succeed. This allows us to attract and retain the best talent, serve clients through diverse thinking, and better represent and support the various communities in which we live and work. Plante Moran is an Equal Opportunity Employer.
Plante Moran maintains a drug-free workplace.
Interested applicants must submit their resume for consideration using our applicant tracking system. Due to the high volume of interest in our positions, only candidates selected for interviews will be contacted. Candidates must be legally authorized to work in the United States without sponsorship, with the exception of qualified candidates who are bilingual in either Japanese and English or Chinese and English. Unsolicited resumes from search firms or employment agencies, or similar, will not be paid a fee and become the property of Plante Moran.
The specific statements above are not intended to be all-inclusive.
We are pleased to offer eligible staff a robust benefits package. Eligibility and contribution requirements for some of these benefits vary based on the number of hours staff work per week. Highlights include health, dental, vision, disability, and life insurance. In addition to this, eligible staff are able to take advantage of our Flexible Time Off and various pre-determined holidays, as well as a 401(k) plan, flexible benefits plans, business-related travel expense, lodging, and meal reimbursement for business-related use. A pension plan is also available for eligible administrative and paraprofessional staff. A discretionary bonus plan is available for eligible staff. Plante Moran also offers some contingent staff positions the option to elect health insurance in addition to limited paid sick time.
The compensation range reflects the base salary we reasonably expect to pay for this position across our offices in the following regions: CO, IL, OH, and MA. Please review the position description for the applicable geographic location. Generally, experienced hires are not hired at or near the maximum salary range, as compensation decisions take into account a wide variety of factors, including but not limited to: responsibilities, education, experience, knowledge, skills, and geography. For early career roles, including campus hires, we offer standardized, market-based starting salaries among individuals within the same hiring group. This approach ensures fairness and reflects current industry benchmarks for entry-level talent.
Under Colorado’s Job Application Fairness Act, you have the right to redact, from any documents that you submit in connection with your application, information that identifies your age, date of birth, or dates of attendance at or graduation from an educational institution. Should you wish to exercise your right to redact such information, please redact it prior to submitting documentation.
The compensation range for this role in CO, IL, OH, and MA is: $82,500 -$137,500.
This application window is a good-faith estimate of the time that this posting will remain open. This deadline will be promptly updated if the deadline is extended.
Salary Context
This $82K-$137K range is in the lower quartile for Data Engineer roles in our dataset (median: $151K across 28 roles with salary data).
Role Details
About This Role
Data Engineers build the pipelines that feed AI models. They design ETL workflows, manage data lakes, and ensure training and inference data is clean, timely, and accessible. Without good data engineering, AI projects fail. It's that simple.
The AI era has expanded the data engineer's scope far beyond batch ETL jobs. You're building real-time embedding pipelines for RAG systems, managing vector databases, ensuring training data quality at scale, and building the infrastructure that lets ML teams iterate on data as fast as they iterate on models. Data quality is the biggest predictor of model quality, and you're the person responsible for it.
Across the 9,653 AI roles we're tracking, Data Engineer positions make up 1% of the market. At Plante Moran, this role fits into their broader AI and engineering organization.
Data Engineer demand in AI contexts is strong and growing. Every company building AI needs clean, reliable data pipelines. The shift toward real-time AI applications (chatbots, recommendation engines, agent systems) means data engineering is more critical than ever. Companies are willing to pay premium salaries for data engineers with AI/ML pipeline experience.
What the Work Looks Like
A typical week includes: debugging a data pipeline that's producing stale embeddings for the RAG system, optimizing a Spark job that processes training data, building a data quality monitoring dashboard, meeting with the ML team to understand their next data requirements, and writing dbt models that transform raw event data into ML-ready features. The work is deeply technical and high-impact.
Data Engineer demand in AI contexts is strong and growing. Every company building AI needs clean, reliable data pipelines. The shift toward real-time AI applications (chatbots, recommendation engines, agent systems) means data engineering is more critical than ever. Companies are willing to pay premium salaries for data engineers with AI/ML pipeline experience.
Skills Required
SQL, Python, and distributed systems (Spark, Airflow, dbt) are core. Cloud data platforms (Snowflake, BigQuery, Redshift) are increasingly standard. Many AI-focused roles also want familiarity with vector databases and embedding pipelines. Understanding data modeling, pipeline orchestration, and data quality frameworks covers the essentials.
AI-specific data engineering skills include: building feature stores, managing training data versioning, implementing data lineage tracking, and building real-time embedding pipelines. Experience with streaming systems (Kafka, Flink) is valuable for real-time AI applications. Understanding ML data requirements (balanced datasets, data augmentation, evaluation set construction) makes you much more effective working with ML teams.
Strong postings specify the data stack, mention ML pipeline work, and describe the scale of data you'll be working with. Look for companies that understand the connection between data quality and model quality. Avoid roles that conflate data engineering with data analysis.
Compensation Benchmarks
Data Engineer roles pay a median of $177,825 based on 160 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $193,200. This role's midpoint ($110K) sits 38% below the category median. Disclosed range: $82K to $137K.
Across all AI roles, the market median is $213,400. Top-quartile compensation starts at $264,230. The 90th percentile reaches $319,400. For comparison, the highest-paying categories include AI Safety ($253,100) and Research Engineer ($252,000). By seniority level: Entry: $110,408; Mid: $193,200; Senior: $228,700; Director: $272,275; VP: $235,000.
Plante Moran AI Hiring
Plante Moran has 1 open AI role right now. They're hiring across Data Engineer. Based in Chicago, IL, US. Compensation range: $137K - $137K.
Location Context
AI roles in Chicago pay a median of $194,700 across 390 tracked positions. That's 9% below the national median.
Career Path
Common paths into Data Engineer roles include Backend Engineer, Database Administrator, Analytics Engineer.
From here, career progression typically leads toward Senior Data Engineer, ML Engineer, Data Platform Lead.
Master SQL and Python first. Then learn a distributed processing framework (Spark or its modern alternatives) and a pipeline orchestrator (Airflow, Dagster, Prefect). Build a portfolio project that demonstrates end-to-end pipeline construction: ingest, transform, validate, serve. If you want to specialize in AI data engineering, add vector databases and embedding pipelines to your skill set.
What to Expect in Interviews
Expect SQL deep-dives (query optimization, partitioning strategies, data modeling), Python coding focused on data pipeline patterns, and system design questions about building scalable ETL workflows. Companies with ML teams will ask about feature stores, embedding pipelines, and training data management. Be ready to discuss data quality monitoring, pipeline orchestration, and how you'd handle schema evolution in a production data lake.
When evaluating opportunities: Strong postings specify the data stack, mention ML pipeline work, and describe the scale of data you'll be working with. Look for companies that understand the connection between data quality and model quality. Avoid roles that conflate data engineering with data analysis.
AI Hiring Overview
The AI job market has 9,653 open positions tracked in our dataset. By seniority: 193 entry-level, 4,500 mid-level, 3,455 senior, and 1,505 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (568 positions). The remaining 9,010 roles require on-site or hybrid attendance.
The market median for AI roles is $213,400. Top-quartile compensation starts at $264,230. The 90th percentile reaches $319,400. Highest-paying categories: AI Safety ($253,100 median, 57 roles); Research Engineer ($252,000 median, 419 roles); AI Engineering Manager ($251,622 median, 51 roles).
Data Engineer demand in AI contexts is strong and growing. Every company building AI needs clean, reliable data pipelines. The shift toward real-time AI applications (chatbots, recommendation engines, agent systems) means data engineering is more critical than ever. Companies are willing to pay premium salaries for data engineers with AI/ML pipeline experience.
The AI Job Market Today
The AI job market spans 9,653 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (7,301), Data Scientist (441), AI Software Engineer (438). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (193) are outnumbered by mid-level (4,500) and senior (3,455) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 1,505 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (568 positions), with 9,010 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $213,400. Top-quartile roles start at $264,230, and the 90th percentile reaches $319,400. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $253,100 median, while Prompt Engineer roles sit at $141,440. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,605 postings), Aws (916 postings), Azure (724 postings), Rag (634 postings), Gcp (522 postings), Pytorch (495 postings), Kubernetes (384 postings), Claude (383 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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