Remote Data Engineer / Databricks / Work - Life Balance

A fast-growing, AI-driven digital consultancy is hiring a Data Engineer to help build modern data platforms for large enterprise clients. This role focuses on technologies like Databricks, Apache Spark (PySpark), and cloud platforms (AWS/Azure), delivering scalable solutions that power analytics and machine learning initiatives. This opportunity stands out for its high impact and variety, so you won’t be siloed. Instead, you’ll design end-to-end pipelines, contribute to cloud lakehouse architectures, and partner closely with analytics and AI teams across multiple industries. It’s ideal for someone who wants to expand their technical depth while working on meaningful, production-level systems that directly influence business outcomes. Required Skills & Experience • 3–5 years of hands-on data engineering experience • Strong experience with Databricks (Delta Lake, workflows, SQL) • Proficiency with Apache Spark (PySpark preferred) • Advanced SQL skills for large-scale data processing • Experience with AWS or Azure data services • Solid understanding of data modeling and architecture patterns • Experience working in Agile environment Desired Skills & Experience • Experience with Delta Live Tables or similar frameworks • Familiarity with dbt or modern transformation tools • Exposure to ML pipelines or feature engineering workflows • Experience with data governance or cataloging tools • Background in consulting or client-facing environments • Experience with streaming data (Kafka or Spark Streaming) What You Will Be Doing Tech Breakdown • 70% Databricks / Spark / Cloud Data Engineering • 30% Data Modeling, Optimization, and Collaboration Daily Responsibilities • 75% Hands-on • 15% Cross-Team Collaboration • 10% Architecture & Design The Offer • Bonus eligible You Will Receive The Following Benefits • Medical, Dental, and Vision Insurance • Flexible Time Off (FTO) • Paid parental leave Applicants must be currently authorized to work in the US on a full-time basis now and in the future. Posted By: Charles Deuter