Data Engineer

Requirements:

• We require a bachelors degree in Computer Science, Data Science, Engineering, or a related discipline; a masters degree is preferred.
• We look for at least 3 years of experience in data engineering, data science, or a blended role.
• We need strong programming capability in Python and SQL.
• We expect experience designing data pipelines and working with large-scale datasets, using tools such as Spark, Airflow, or similar platforms.
• We require hands-on exposure to cloud environments such as AWS, Azure, or GCP.
• We value familiarity with machine learning libraries and frameworks such as scikit-learn, TensorFlow, or PyTorch.
• We need experience with data visualization and business intelligence tools.
• We seek strong analytical problem-solving skills and the ability to explain technical ideas to non-technical audiences.
• Preferred experience includes containerization and orchestration tools such as Docker and Kubernetes.
• Preferred experience includes data warehousing platforms such as Snowflake, Redshift, or BigQuery.
• Preferred knowledge of MLOps practices and model deployment workflows.
• Preferred experience working in Agile or Scrum environments.

Responsibilities:

• We design, develop, and support scalable data pipelines and ETL/ELT processes that power analytics and machine learning work.
• We build and refine data architectures in both cloud-based and on-premises environments.
• We examine large, complex data sources to uncover insights that inform business strategy.
• We develop, train, and deploy machine learning models for forecasting, classification, and optimization use cases.
• We partner with product, engineering, and business teams to turn data requirements into practical technical solutions.
• We help maintain data accuracy, consistency, and governance across our systems.
• We create dashboards, visual summaries, and reports using BI tools such as Power BI or Tableau.
• We continuously evaluate our data workflows and recommend improved tools, technologies, and methods.

Technologies:

• Airflow
• AWS
• Redshift
• Azure
• BigQuery
• Business Intelligence
• Cloud
• Docker
• ETL
• GCP
• Support
• Kubernetes
• Machine Learning
• Power BI
• PyTorch
• Python
• SQL
• Snowflake
• Spark
• Tableau
• TensorFlow

More

We are a growing, data-driven organization located just north of downtown Pittsburgh, and we offer a hybrid work arrangement with 2–3 days onsite in our modern office. This full-time direct-hire role combines data engineering, analytics, and machine learning, giving you the chance to contribute across the full data lifecycle while working on high-impact initiatives with advanced tools. We provide a competitive salary, comprehensive benefits, and a collaborative, innovative environment with strong opportunities for professional growth. We are committed to fostering an inclusive workplace and encourage qualified candidates from all backgrounds to apply.

last updated 44 week of 2026