Position Overview

We are looking for a talented Data Engineer to join Stanley’s Enterprise Data Platform team. In this role, you will contribute to projects and initiatives across the business. You will ensure data is available and consumable a wide range of users, ranging from the ingestion of source data to creating data visualizations. If you want to be part of building a data platform to support a dynamic, growing, business we’d love to hear from you!

What You'll Do

Design, develop, and maintain end-to-end business intelligence (BI) and analytics solutions using Microsoft Azure data migration, storage, compute, and data visualization technologies.

Develop end-to-end solutions for performant ingestion, storage, processing, and integration of disparate sourced data.

Use Python to manipulate and analyze complex datasets.

Build data visualizations that effectively communicate insights to diverse audiences.

Test, audit, maintain and tune existing solutions.

Monitor daily data loads and resolve issues; update and extend system documentation.

Who You Are

Strong analytical skills with the ability to collect, organize, analyze, and disseminate significant amounts of information with attention to detail and accuracy.

Experienced user of Azure Data Storage and Analytics.

Possess a good understanding of data architecture principles and practices.

Knowledgeable about data warehouse design and data mining.

Proficient in coding languages like SQL, Python, PySpark and/or R.

Comfortable with a variety of data visualization tools and techniques.

Education and Experience

Bachelor’s degree in Computer Science, Computer Engineering, Mathematics, Statistics or a related field; graduate degree in Data Engineering, Data Analytics, Data Science or other quantitative field is preferred.

5+ years of data engineering and/or BI developer experience is required, preferably in a cloud environment.

Microsoft Certified: Azure Data Engineer Associate.

Experience with Azure Data Storage and Analytics tool stack (including Data Lake, Data Factory, Synapse Analytics and Microsoft Fabric) is required.

Experience working with various data formats (structured, semi-structured, unstructured and API-exposing).

Experience with defining connections to and extracting data from Enterprise Resource Planning (ERP) systems (including Oracle EBS, SAP, etc.) preferred.

Experience with Synapse ML preferred.

Understanding of manufacturing, supply chain, inventory management, eCommerce and sales operations data and systems preferred

Software Concepts

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