Kenway Consulting

Management and technology consulting services

Data Analytics & Cloud Engineering Consultant

Data EngineeringUpdated on Nov 13

Full-timeChicago, IL, USA$95k - $115k /yr

About the Job

Requirements

Qualification in data analytics, information management, computer science, or equivalent practical experience.
1–3 years of experience, including internships or co-ops, building, implementing, and maintaining data solutions on modern data platforms.
Working understanding of core Microsoft Azure data services, such as storage, compute, Synapse, and OneLake, and how they support a data platform; hands-on exposure to provisioning and configuring cloud resources, managing access and secrets with role-based access control, managed identities, and Key Vault, and building with cost and security in mind.
Hands-on exposure to Databricks and/or Microsoft Fabric, including building and running data pipelines and developing in notebooks.
Proficiency in Python and SQL, including real data analysis and SQL performance and tuning fundamentals.
Ability to explore data, investigate anomalies, reason from symptoms to root cause, and clearly explain findings about what the business is seeing.
Exposure to AI in the modern data and analytics stack, including AI-assisted and conversational analytics, large language models applied to data problems, or AI coding assistants, and curiosity to keep pace with evolving tools.
Understanding of CI/CD and DevOps for data, 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; and familiarity with tools such as Azure DevOps, GitHub Actions, dbt, Databricks Asset Bundles or 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, such as dbt.
Exposure to Agile ways of working and delivery tools such as JIRA or Azure DevOps Boards.
Ability to connect technical work to the business problem it solves, take ownership of defined work, and deliver value with limited oversight.

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 findings clearly.
Write clean, well-structured Python and SQL to move, model, transform, and analyze data.
Apply software-delivery discipline to data assets through version control, testing, and CI/CD-based deployment across environments.
Take ownership of defined technical tasks and deliver them with increasing independence.
Support proposals, demos, and collateral used in business-development pursuits.
Understand clients’ businesses, build working relationships, and help solve their technology and business problems.

About This 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.

Core Traits We Are Seeking

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.

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

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

About the Company

Kenway Consulting

Management and technology consulting services

Kenway Consulting helps organizations improve performance by offering management and technology consulting services. The firm specializes in Technology Solution Delivery, Enterprise Program Leadership, and Information Insight, delivering projects and programs that align with business goals and technology needs. Its approach centers on guiding principles like integrity, quality, value, and respect, and it focuses on the way work is done—the methods and ethics—rather than just the end results. The company works with clients to plan, manage, and execute technology-enabled initiatives, providing leadership, governance, and data-driven insights to ensure successful outcomes. Kenway’s goal is to provide unmatched quality and service by staying true to its principles, helping both clients and their employees succeed.

Company size: 51-200
Company stage: Not listed
Total funding: Not listed
Headquarters: Chicago, IL
Founded: 2004

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