Data Engineer

Amplifi Group, LLC•Appleton, WI

4d•Hybrid

About The Position

Amplifi is the go-to data consultancy for enterprise organizations that want their success to be driven by data. We empower our clients to innovate, grow and succeed by establishing and delivering strategies across all elements of the data value chain. From the governance and management of data through to analytics and automation, our integrated approach to modern data ecosystems delivers measurable results through a combination of expert consultancy and best-in-breed technology. Our company and team members are proud to empower our clients’ businesses by providing exceptional solutions and value, as we truly believe their success is our success. We thrive on delivering excellent solutions and overcoming technical and business challenges. As such, we’re looking for like-minded individuals to learn, grow, and mentor others as a part of the Amplifi family. The Data Engineer will be responsible for designing, building, and maintaining scalable, secure data pipelines that drive analytics and support operational data products. The ideal candidate brings a strong foundation in SQL, Python, and modern data warehousing with a deep understanding of Snowflake, Databricks, or Microsoft Fabric, and a solid understanding of cloud-based architectures.

Requirements

4+ years of experience in a data engineering or related software engineering role.
Proficiency in SQL and Python for data manipulation, transformation, and scripting.
Strong experience working with Snowflake and MSSQL Server.
Practical knowledge of working with cloud data platforms, especially Microsoft Azure.
Experience with modern data modeling and warehouse optimization techniques.
Ability to work independently and with a team in a hybrid/remote environment.

Nice To Haves

Experience with Databricks, Azure Data Factory, or DBT preferred.
Exposure to Microsoft Fabric components like OneLake, Pipelines, or Direct Lake.
Familiarity with cloud services across AWS, GCP, or hybrid cloud environments.
Understanding of or curiosity about Dataiku for data science and advanced analytics collaboration.

Responsibilities

Design, develop, and optimize robust ETL/ELT pipelines to ingest, transform, and expose data across multiple systems.
Build and maintain data models and warehouse layers, enabling high-performance analytics and reporting.
Collaborate with analytics, product, and engineering teams to understand data needs and deliver well-structured data solutions.
Write clean, efficient, and testable code in SQL and Python to support automation, data quality, and transformation logic.
Support deployment and orchestration workflows, using Azure Data Factory, dbt, or similar tools.
Work across multi-cloud environments (Azure preferred; AWS and GCP optional) to integrate data sources and manage cloud-native components.
Contribute to CI/CD practices and data pipeline observability (monitoring, logging, alerting).
Ensure data governance, security, and compliance in all engineering activities.
Support ad hoc data science and machine learning workflows within Dataiku.