Data, Analytics & Cloud Engineering Consultant

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

Ability to chart your individual career path based on your expertise and passions.

An environment that encourages you to identify new opportunities and provides support to make them happen.

A balanced lifestyle through a flexible consulting model working with local (Chicagoland) and national clients.

The opportunity to build and be part of a fun and collaborative team.

Kenway Consulting is a management and technology consulting firm whose entire reason for existence is to help companies and its employees.

Chicago, Illinois, USA

https://www.kenwayconsulting.com/

Distribution of Different Job Fields Receiving Sponsorship

46

Represents job field similar to this job

Management and Executive

Engineering and Development

Customer Service and Support

Trends of Total Sponsorships

*2026

(3)

2025

(4)

2024

(6)

2023

(5)

2022

2021

(2)

2020

Growth Stage

Leadership Team

Matt Kueker

Executive Vice President - Strategic Growth

Qualifications

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

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

Required skills

Microsoft Azure Cloud Engineering, Databricks, Microsoft Fabric, Python, SQL, CI/CD, Git, ETL/ELT, Data Lakehouse, Data Modeling, Large Language Models, dbt

Preferred skills

Analytical Problem-Solving

Experience

1+ years