Analytics Engineer II

CDW

About The Position

At CDW, we make it happen, together. Trust, connection, and commitment are at the heart of how we work together to deliver for our customers. It’s why we’re coworkers, not just employees. Coworkers who genuinely believe in supporting our customers and one another. We collectively forge our path forward with a level of commitment that speaks to who we are and where we’re headed. We’re proud to share our story and Make Amazing Happen at CDW. Job Summary The Analytics Engineer II plays a pivotal role in designing, building, and operationalizing data solutions that power analytics, reporting, and data‑driven decision‑making across the enterprise. This role blends software engineering rigor with analytics‑focused data modeling by developing scalable data pipelines, transforming raw data into consumable datasets, and supporting analytics teams with well‑structured, high‑quality data assets. The Analytics Engineer II partners closely with business and technical teams to improve data models, enhance data accessibility, and automate complex data preparation tasks using modern cloud platforms and engineering best practices.

Requirements

BS degree in Computer Science, Information Systems, Business Analytics, or a related technical field and 3 years of data application development experience using Azure Data Factory/Fabric Data Factory or SSIS, 5+ years of data application development experience using Azure Data Factory/Fabric Data Factory or SSIS.
Experienced researching technical and business questions with minimal oversight.
Intermediate to advanced SQL and/or Python skillsets to transform and analyze data, building or supporting data pipelines, and delivering datasets used for reporting or analytics.
Experience in developing Power BI data models and dashboards
Ability to work independently on moderately complex tasks.
Ability to effectively communicate and collaborate with business partners and technical teams.
Experience in Agile project management methodologies
Experience experimenting with AI agents, LLM‑based tools, or prompt‑driven automation to enhance analytics or data workflows

Responsibilities

Build and optimize full‑stack, cloud‑based data systems and pipelines that deliver high‑quality, analysis‑ready datasets for business and analytics teams
Interface with other technology teams to build Azure Data Pipelines to integrate with Data Lake and other enterprise platforms
Enhance ingestion, transformation, and orchestration workflows aligned with enterprise architecture standards
Collaborate with other technology teams to help engineer data sets and curate semantic models that support analytics, machine learning, KPI reporting, and business intelligence use cases.
Partners with business teams to enhance data models supporting business intelligence tools, increase data accessibility, and foster data-driven decision-making throughout the organization.
Partner with analysts and data scientists to translate business requirements into scalable engineering solutions that improve data accessibility and reliability.
Share your passion for staying on top of tech trends, experimenting with and learning new technologies, participating in internal & external technology communities, mentoring other members of the engineering community.
Collaborate with digital product managers and deliver robust cloud-based solutions that drive powerful experiences and support enterprise‑wide analytics decision‑making
Responsible for using innovative and modern tools, techniques, and architectures to partially or completely automate the most-common, repeatable, and tedious data preparation and integration tasks to minimize manual and error-prone processes and improve productivity.
Be curious and knowledgeable about new data management techniques and how to apply them to solve business problems.
Document data flows, transformations, and modeling logic to promote consistency and trust in delivered datasets.