Data Engineer (Databricks)

Motion Recruitment

Town of Texas (WI)

Remote

USD 110,000 - 150,000

Full time

4 days ago
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Benefits offered by this job

Medical Insurance
Dental Insurance
Vision Insurance
Vacation Time
Stock Options
Salary Bonus
PTO & Paid Holidays
401(k) with Company Match
Remote
Growth & Leadership Opportunity

Job summary

Motion Recruitment is seeking a Data Engineer for a full-time, remote opportunity supporting a leading research, analytics, and technology organization in the utility/energy sector. You will design, build, and optimize modern data solutions using Databricks, Spark, Python, AWS, SQL, and PostgreSQL to support data products and analytics.

You’ll join a collaborative ML Engineering team, mentoring others and expanding cloud data platform skills while delivering scalable data platforms that enhance

Qualifications

  • 5+ years in Data Engineering or related field.
  • Expert Python, SQL; Databricks and Spark proficiency.
  • Experience building cloud-based pipelines in AWS.
  • Knowledge of governance, security, privacy and retention.

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 and improve data quality, reliability, and availability.

Skills

Databricks
Spark
Python
SQL
AWS
PostgreSQL

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
What You Will Be Doing

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.

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