Senior Data Engineer

Role Description

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.

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).