Senior Databricks Data Engineer - Oil & Gas

Data Elephant; Calgary; On-site; CAD 120,000 - 180,000; Full time

Job summary

Data Elephant in Calgary is seeking a Senior Databricks Data Engineer to design end-to-end data pipelines and AI-ready pipelines for industrial data in Oil & Gas. You will build scalable ETL processes, develop Azure Databricks foundations, and collaborate with Field Engineers and SMEs to translate domain knowledge into technical solutions.

Ideal candidates bring strong background in time-series data, telemetry, and complex SQL/Python/Spark, plus experience with data governance, lineage, and

Qualifications

• Senior-level experience designing and developing production data pipelines with Azure Databricks.
• Experience with complex SQL, Python, Spark.
• Experience with incremental processing and time-series data.
• Knowledge of data governance, lineage, and auditable calculations.

Responsibilities

• Design, build, and optimize pipelines for sensor and related operational data.
• Develop complex transformation and calculation logic based on engineering requirements.
• Implement robust incremental-processing patterns for high-volume and continuously changing datasets.
• Design, build, and deploy end-to-end AI/ML solutions in production environments.
• Develop robust backend systems and APIs to support AI-driven applications.
• Build and maintain data pipelines and feature engineering workflows.
• Implement and operationalize machine learning models (training, deployment, monitoring).
• Work with modern AI tooling (LLMs, agents, orchestration frameworks).
• Collaborate with clients to translate business problems into technical solutions.
• Contribute to architecture decisions and best practices across projects.
• Mentor client team members and contribute to internal capability building.
• Work directly with engineering and operational SMEs to understand physical processes and translate their knowledge into technical requirements.
• Make engineering calculations and data transformations explainable, traceable, testable, and auditable.
• Document data lineage, calculation logic, assumptions, dependencies, and exception-handling rules.

Skills

Data pipeline design

Python

SQL

Spark

Time-series data handling

SME collaboration

Education

Engineering or applied-science degree

Tools

Azure Databricks

Databricks dashboards

Genie

Excel/CSV integration

Job description

We are looking for a Senior Databricks Data Engineer to join our team.

This role is ideal for someone who enjoys building end-to-end solutions and wants to work on real-world industrial use cases that comes from an Engineering background, and has experience in Oil & Gas.

In this position, you’ll contribute to a variety of impactful client projects, including:

• Building AI-powered anomaly detection systems for operational and industrial data
• Modernizing asset management workflows
• Developing natural language interfaces for querying enterprise and operational data
• Implementing Azure Databricks foundations and pipelines with best practices
• Creating scalable data pipelines and ML workflows in cloud environments
• Enabling real-time and batch data processing for analytics and AI use cases
• Working through complex and challenging data conditions, including incremental processing, late-arriving or changing records, complex business and engineering rules, and reconciliation of results across processing runs

The ideal candidate combines strong data engineering experience with an engineering or applied-science background. Direct experience industrial time-series data, scientific measurements, telemetry, financial reconciliation, or other datasets where accuracy, traceability, and incremental recalculation are critical.

Key Responsibilities

• Design, build, and optimize pipelines for sensor and related operational data.
• Develop complex transformation and calculation logic based on engineering requirements.
• Implement robust incremental-processing patterns for high-volume and continuously changing datasets.
• Design, build, and deploy end-to-end AI/ML solutions in production environments
• Develop robust backend systems and APIs to support AI-driven applications
• Build and maintain data pipelines and feature engineering workflows
• Implement and operationalize machine learning models (training, deployment, monitoring)
• Work with modern AI tooling (LLMs, agents, orchestration frameworks)
• Collaborate with clients to translate business problems into technical solutions
• Contribute to architecture decisions and best practices across projects
• Mentor client team members and contribute to internal capability building
• Work directly with engineering and operational SMEs to understand physical processes and translate their knowledge into technical requirements.
• Make engineering calculations and data transformations explainable, traceable, testable, and auditable.
• Document data lineage, calculation logic, assumptions, dependencies, and exception-handling rules.

Ideal Background

• Senior-level experience designing and developing production data pipelines with Azure Databricks including strong experience with complex SQL, Python, Spark, or comparable data-processing technologies.
• Complex Excel and CSV integration experience
• Experience with Databricks dashboards and Genie
• Strong requirements gathering experience with Field Engineers and Technical SMEs
• Demonstrated experience with incremental processing, change detection, reconciliation, and pipeline design
• Experience handling time-series, telemetry, sensor, operational, scientific or industrial data
• Medallion architecture and modelling
• Strong analytical and investigative skills, with the patience to work through detailed logic and difficult data-quality problems.
• Degree or professional background in petroleum, reservoir, chemical, mechanical, geological, geophysical, or another relevant engineering or applied-science discipline is strongly preferred.
• Experience in upstream oil and gas, thermal operations, SAGD, well surveillance, production engineering, or subsurface data would be a significant asset.

This role presents an exciting opportunity to work on practical, high-impact AI use cases - not just prototypes, shape how AI is applied to client environments, and change the game on traditional processes and platforms. Come join a growing organization helping clients take a new, lean and value-driven approach to data and engineering!