AWSCloudDockerPySparkPythonSparkSQLMachine LearningData EngineeringData LakeAnalyticsDatabricksGitSource ControlAgileCI/CDCommunicationCollaborationRemote Work
About this role
Role Overview
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
Requirements
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