About Eureka Labs
At Eureka Labs, we create simple solutions to complex problems. We build -and scale-tech products and teams for fast-growing marketplaces and SaaS companies while creating an enjoyable experience for team members and our global growth partners.
We are a team of more than 100 people working from Latin America, the USA, and Europe for companies based mostly in NA and EMEA. Our mission is to be the growth partner they choose to delight their customers.
Our values -Think, Build, Enjoy- are a reflection of our DNA: an organization where talented people can grow, challenge themselves, and take their careers to the next level over and
over again.
We encourage each member of our team to maintain a healthy work-life balance, and we all enjoy benefits such as flexible work arrangements, remote work, training and development programs, and a time off policy.
We are just a group of people who also happen to be some of the brightest talents around.
Let's choose each other!
About our Growth Partner
Our Growth Partner is a leading research, consulting, and technology company focused on helping utilities navigate constant change and growing complexity. By combining deep industry expertise with advanced analytics, software, and data-driven insights, they enable utilities to better serve their customers, optimize grid operations, and accelerate the energy transition.
With a strong commitment to innovation and measurable outcomes, they leverage modern data platforms and artificial intelligence to transform how utilities operate and make decisions. As they continue to expand their internal AI capabilities, they are investing in scalable, production-ready solutions that support smarter, more efficient, and more sustainable energy systems.
About the Position
Overview
Location: Full remote
Schedule: Full time -
Job Purpose
We are looking for a Senior Data Engineer to join E Source’s Data Engineering team. This is a hands-on individual contributor role focused on designing, building, optimizing, and maintaining scalable, reliable, and secure data platforms, pipelines, and infrastructure that support both internal initiatives and client-facing solutions.
The ideal candidate brings deep experience with Databricks, Spark, cloud-based data platforms, and distributed data processing. While this is not a people management role, the engineer is expected to provide technical guidance and mentorship to less experienced team members when appropriate.
You will collaborate closely with data engineers, architects, data scientists, analysts, and cross-functional stakeholders to deliver high-quality data solutions that support analytics, machine learning, and business objectives.
Responsibilities
● Design, build, and maintain scalable data pipelines and data platforms using Databricks, Spark, Python, SQL, and cloud technologies.
● Develop, optimize, and support both batch and streaming data processing solutions.
● Implement and maintain reliable, secure, and high-performance data workflows, including orchestration, monitoring, and operational support.
● Build and evolve data lake and lakehouse solutions to support analytics, reporting, and machine learning initiatives.
● Collaborate with architects, data engineers, data scientists, analysts, and business stakeholders to translate requirements into scalable technical solutions.
● Ensure data quality, integrity, availability, and performance across data platforms and pipelines.
● Contribute to the definition and adoption of data engineering standards, best practices, and design patterns.
● Participate in software development lifecycle activities, including source control, testing, CI/CD, deployment, and operational support.
● Evaluate emerging technologies, tools, and best practices to continuously improve the data platform.
● Provide technical guidance and mentorship to junior engineers when needed.
Experience & Qualifications
● 6+ years of experience in Data Engineering or a related field.
● Strong hands-on experience with Databricks in production environments.
● Strong experience with Spark (PySpark preferred), distributed data processing, and large-scale data workloads.
● Advanced proficiency in Python and SQL.
● Experience designing and building cloud-based data platforms and pipelines (AWS preferred).
● Experience developing and supporting both batch and streaming data processing solutions.
● Experience optimizing, troubleshooting, and tuning data pipelines and data platforms.
● Experience building and maintaining Data Lake and/or Lakehouse architectures.
● Familiarity with data governance, data quality, data lineage, security, privacy, and retention practices.
● Experience working in Agile environments and collaborating with
cross-functional teams.
● Strong ability to work autonomously, take ownership of technical solutions, and provide technical guidance to other engineers when needed.
● Experience with workflow orchestration tools and modern software development practices, including Git, Docker, and CI/CD.
● Experience supporting Machine Learning, Analytics, or Data Science initiatives is a plus.
● Experience in the utilities, energy, or related industries is a plus.
● Strong communication, collaboration, and problem-solving skills.
● Advanced English level (written and spoken).