Senior Data Engineer
Clearlight Energy
- Houston, Texas, United States
- Houston, Texas, United States
À propos
Clearlight Energy focuses on providing operational excellence to supply critical energy capacity and meet growing demand. Additionally, it has a 1,200 MW development pipeline of additional renewable resources to support grid reliability and decarbonization
About the Role: We are looking for a Senior Data Engineer to join our data team and help build and maintain the infrastructure that moves data from source to insight. You will work across our full data stack — ingesting data from AVEVA PI, Bazefield, and a range of APIs and external connections into our Microsoft Fabric data lake, managing the flow through Bronze, Silver, and Gold layers, and delivering clean, reliable data to Power BI for reporting and automated distribution.
This is a hands-on role with real ownership from day one. You will be responsible for keeping pipelines healthy, data layers well-structured, and reports accurate and on schedule. You will work closely with the Operational Technology (OT) team, business stakeholders, and senior engineers to ensure our data platform is robust, scalable, and well-documented. This role reports to the Manager of Data & Applications.
The Company follows a hybrid work model, with employees in the office from Tuesday through Thursday. Location: Oakville, ON or Houston, TX.
Job Summary: Responsible for developing end-to-end data pipelines, managing data lake architecture, and delivering high-quality data for reporting and analytics. The ideal candidate will bring strong technical expertise, a proactive mindset, and a commitment to data quality, working cross-functionally with internal teams to support business insights and operational reporting.
Key Responsibilities
Design, build, and maintain data pipelines to ingest, transform, and deliver data across multiple sources Manage and optimize the data lake architecture, ensuring consistency across Bronze, Silver, and Gold layers Develop and maintain data models to support reporting and analytics needs Integrate data from APIs, databases, and third-party systems into the data platform Ensure data accuracy, consistency, and reliability through validation and monitoring processes Implement monitoring, alerting, and troubleshooting for data pipelines and workflows Manage data lifecycle processes including retention, backfilling, and historical data corrections Build and maintain Power BI datasets and support automated reporting solutions Collaborate with cross-functional teams to translate business requirements into technical solutions Maintain clear documentation of data pipelines, models, and system architecture Participate in code reviews, technical discussions, and continuous improvement initiatives Ensure adherence to data governance, security, and best practices
Required Qualifications
Minimum 4 years of experience in data engineering, analytics engineering, or a related technical role. Solid SQL skills — comfortable with joins, window functions, aggregations, and data transformation. Solid knowledge of Python, particularly for data manipulation and API interactions. Skilled in data lake concepts and layered architecture (Bronze / Silver / Gold or equivalent). Familiarity with REST API concepts — pagination, authentication, incremental pulls. Skilled in cloud data platforms (Microsoft Fabric, Azure, AWS, or GCP). Hands-on experience with Microsoft Fabric — Lakehouses, Pipelines, Dataflows Gen2, Spark Notebooks, or Warehouses. Familiarity with AVEVA PI, PI Asset Framework (AF), or PI DataLink at any level. A strong sense of data reliability — you care about completeness, freshness, and accuracy. Clear written communication and a habit of documenting your work. Experience providing leadership and day-to-day guidance to team members, including mentoring, building strong relationships, and performance support. Post-secondary education in Computer Science, Engineering, Data Science, or equivalent practical experience.
Qualifications
Minimum 4 years of years of experience in data engineering or a related technical field Strong proficiency in SQL and experience with data transformation techniques Hands-on experience with Python for data processing and integrations Solid understanding of data lake architecture and modern data engineering practices Experience working with cloud data platforms (e.g., Microsoft Fabric, Azure, AWS, or GCP) Familiarity with API integrations and data ingestion frameworks Strong attention to data quality, accuracy, and performance Excellent communication and documentation skills
Compétences linguistiques
- English
Avis aux utilisateurs
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