Data Engineer (Databricks)

Motion Recruitment; United States; Remote; USD 110,000 - 160,000; Full time

Benefits offered by this job

Health benefits

Vacation Time

Stock Options

Bonus Eligible

PTO & Holidays

401(k) Matching

Remote

Growth Leadership

Job summary

Motion Recruitment is seeking a Data Engineer for a fully remote, full-time role supporting a leading research and analytics organization in the utilities sector. You will design, build, and optimize modern data solutions using Databricks, Spark, Python, AWS, SQL, and PostgreSQL to power client-facing and SaaS data products.

You will join a collaborative ML Engineering team, working with data scientists, engineers, and analysts to deliver scalable data platforms that improve customer engagement,

Qualifications

• 5+ years of experience in Data Engineering or related field.
• Expert-level proficiency in Python, SQL, Databricks, and Spark.
• Experience building cloud-based data pipelines in AWS.
• Strong understanding of data governance, security, privacy, and retention practices.

Responsibilities

• Design, develop, and maintain scalable data pipelines and infrastructure.
• Build and support data lakes, analytics platforms, and data products.
• Collaborate with cross-functional teams to deliver business-driven solutions.
• Monitor, troubleshoot, and improve data quality, reliability, and availability.

Skills

Python

SQL

Databricks

Spark

AWS

Education

Master's degree in STEM

Tools

AWS

Job description

Seeking a Data Engineer for a full-time opportunity supporting a leading research, analytics, and technology organization within the utility and energy industry. This role will focus on designing, building, and optimizing modern data solutions leveraging Databricks, Spark, Python, AWS, SQL, and PostgreSQL to support both client-facing and SaaS-based data products. The position offers the opportunity to work on large-scale data platforms that help utilities improve customer engagement, grid operations, and business performance.

You'll join a highly collaborative Machine Learning Engineering team where you'll work alongside data scientists, machine learning engineers, analysts, and software engineers to build impactful data solutions. This role is ideal for someone who enjoys solving complex data challenges, mentoring other engineers, and expanding their expertise in cloud data platforms, analytics, and machine learning technologies while contributing to meaningful work within the evolving energy sector. This is a fully remote oppurtunitiy.

Required Skills & Experience

• 5+ years of experience in Data Engineering or a related field
• Expert-level proficiency in Python, SQL, Databricks, and Spark
• Experience building cloud-based data pipelines in AWS
• Strong understanding of data engineering best practices and scalable architectures
• Knowledge of data governance, security, privacy, and retention practices

Desired Skills & Experience

• Experience optimizing ETL workflows within Databricks
• Knowledge of data lineage and data quality frameworks
• Experience supporting machine learning and data science initiatives
• Prior experience within the utility or energy industry
• Master's degree in a related STEM field

Tech Breakdown

• 40% Databricks & Spark Development
• 30% Data Pipeline Engineering
• 20% AWS Data Platform & Infrastructure
• 10% Collaboration, Mentorship & Innovation

Daily Responsibilities

• Design, develop, and maintain scalable data pipelines and infrastructure
• Build and support data lakes, analytics platforms, and data products
• Collaborate with cross-functional teams to deliver business-driven solutions
• Monitor, troubleshoot, and improve data quality, reliability, and availability

The Offer

You will receive the following benefits:

• Medical, Dental, and Vision Insurance
• Vacation Time
• Stock Options
• Eligible for salary bonus
• PTO & Paid Holidays
• 401(k) with Company Match
• Remote
• Strong Growth & Leadership Opportunity

Applicants must be currently authorized to work in the US on a full-time basis now and in the future.