Data, Analytics & Cloud Engineering Consultant

Kenway Consulting • Chicago, IL

5d • Hybrid

About The Position

Kenway Consulting is currently looking for a Data, Analytics & Cloud Engineering Consultant. Above all, this is a consulting role: our consultants are trusted advisors who take the time to understand each client’s business, build strong working relationships, and help solve their critical technology and business problems. Data, analytics, and cloud engineering are the disciplines through which this Consultant will deliver that value — building solutions on modern cloud data platforms and, just as importantly, analyzing the data itself to investigate root causes and interpret what the business is seeing. The Consultant should have a passion for helping clients make better decisions with data, along with the communication skills and professionalism to represent Kenway well. This is an early-career role, and the Consultant will work closely with a collaborative team of senior engineers and architects who will support their growth into a well-rounded, client-facing advisor. They should enjoy working with a collaborative team and for clients of varying sizes and industries, and be eager to take ownership of their work.

Requirements

• Qualification(s) in data analytics, information management, computer science, or equivalent practical experience
• 1–3 years of experience (including internships / co-ops) building, implementing, and maintaining data solutions on Modern Data Platforms, inclusive of the following:
• Cloud architecture and engineering, with a focus on Microsoft Azure — a working understanding of core Azure data services (e.g., storage, compute, Synapse, OneLake) and how they combine to support a data platform, plus hands-on exposure to cloud engineering practices such as provisioning and configuring resources, managing access and secrets (RBAC, managed identities, Key Vault), and building with cost and security in mind
• Hands-on exposure to modern data platforms, specifically Databricks and/or Microsoft Fabric — building and running data pipelines and developing in notebooks
• Proficiency in Python and SQL , with a demonstrated ability to perform real analysis — not just query data — including SQL performance and tuning fundamentals
• Analytical problem-solving — the ability to explore data, investigate anomalies, reason from symptoms to root cause, and translate findings into a clear explanation of what the business is seeing
• Exposure to AI in the modern data and analytics stack — familiarity with how AI is reshaping data work, such as AI-assisted and conversational analytics (e.g., Databricks Genie, Microsoft Fabric Copilot / Data Agents), applying large language models to data problems, and using AI coding assistants to work more effectively, with the curiosity to keep pace as these tools evolve
• An understanding of how CI/CD and DevOps should work in the data space , including: Git-based version control of pipelines, notebooks, and data models, Promoting code across development, test, and production environments, Automated testing, logging, and alerting for data pipelines
• Familiarity with relevant tooling (e.g., Azure DevOps, GitHub Actions, dbt, Databricks Asset Bundles / Repos, or Fabric deployment pipelines)
• Working knowledge of ELT/ETL approaches, including batch and, ideally, real-time or event-driven processing
• Familiarity with Data Lake, Data Lakehouse, and Data Warehouse concepts
• Familiarity with data modeling and data transformation (e.g., dbt)
• Exposure to Agile ways of working and delivery tooling such as JIRA or Azure DevOps Boards
• Business acumen — able to connect technical work to the business problem it solves, and to take ownership of defined work and deliver value with limited oversight

Nice To Haves

• Entrepreneurship: Passion to fuel growth by helping clients, peers, the organization, and yourself, with a continuous hunger to learn.
• Tenacity: Ability to drive through ambiguity.
• Professional Presence: Clear, concise, and articulate when using written and verbal channels.
• Communication: Adept at communicating quickly and effectively, whether the message is good or bad.
• Aptitude: You climb steep learning curves quickly.
• Integrity: Comfortable doing what is right for the project even when doing so may not be the most favorable path forward.
• Growth Mindset: Proactively develop core skills independently and with the help of others.

Responsibilities

• Build and maintain scalable, performant, and cost-effective data pipelines, notebooks, and data products (including Power BI reports) on modern cloud data platforms, under the direction of senior engineers and architects
• Analyze data to investigate problems, identify root causes, and interpret what the business is seeing — then communicate those findings clearly
• Write clean, well-structured Python and SQL to move, model, transform, and analyze data
• Apply software-delivery discipline to data assets — version control, testing, and CI/CD-based deployment across environments
• Take ownership of defined technical tasks and deliver them with increasing independence
• Support the proposals, demos, and collateral leveraged in business development pursuits

Benefits

• A competitive compensation package and exceptional benefits.

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Education Level: Associate degree