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Data Analytics Engineer - Job Opportunity at ARC Resources Ltd.

Calgary, Canada
Full-time
Senior
Posted: July 7, 2025
On-site
CAD 120,000 - 150,000 per year. This estimate is based on the senior-level requirements (7+ years experience), specialized oil and gas industry knowledge, advanced machine learning skills, and Calgary's position as a major energy hub in Canada. The salary range reflects the premium for combining data science expertise with domain knowledge in the energy sector.

Benefits

Comprehensive extended health care coverage providing medical, dental, and vision benefits beyond basic provincial coverage
Market-competitive total compensation structure with performance-based salary adjustments and merit increases
Eligibility for annual performance bonus programs tied to individual and company achievements
Long-term incentive programs including stock options and equity participation for wealth building
Top-tier wellness and healthcare spending accounts for personalized health and fitness expenses
Comprehensive savings plans including retirement contributions and investment matching programs
Professional development opportunities through collaboration with industry experts and continuous learning initiatives
Work-life balance support through health and well-being focused workplace policies

Key Responsibilities

Lead the identification, collection, and transformation of enterprise-scale datasets into strategic business insights using advanced statistical techniques, machine learning models, and predictive analytics that directly impact operational decision-making across multiple business units
Architect and maintain robust data pipelines ensuring efficient data ingestion, processing, and storage systems that support real-time analytics and business intelligence across oil and gas operations
Design, implement, and continuously iterate on predictive models and algorithms that optimize operational performance, reduce costs, and support strategic business growth initiatives with measurable ROI
Collaborate with cross-functional teams including Engineering, Drilling, Completions, Geosciences, Marketing, and Environmental departments to deploy machine learning solutions and automate critical business processes
Develop comprehensive dashboards, visualizations, interfaces, and reports that effectively communicate complex analytical results to executive leadership and non-technical stakeholders for strategic decision-making
Translate complex business challenges into data-driven solutions while proactively identifying new opportunities for innovation and operational efficiency improvements
Support the delivery and adoption of new analytics tools and workflows across the organization, ensuring successful implementation and user adoption
Work within agile frameworks to rapidly prototype, test, and refine analytical solutions while maintaining high standards for code quality, version control, and MLOps best practices
Stay current with cutting-edge analytics, AI/ML, and data engineering trends to continuously advance ARC's data science capabilities and maintain competitive advantage

Requirements

Education

A bachelor's or master's degree in computer science, data science, statistics, engineering, or a related field

Experience

A minimum of 7 years of experience working with large datasets, predictive models, dashboards, and visualizations to develop data-driven solutions

Required Skills

Working with large datasets, predictive models, dashboards, and visualizations Building and deploying machine learning models, such as regression, classification, time series, or deep learning Programming languages such as Python, R, or SQL Cloud-based data platforms Big data technologies, data pipelines, and real-time/batch processing frameworks Databricks Strong problem-solving skills Excellent communication skills
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Sauge AI Market Intelligence

Industry Trends

The oil and gas industry is experiencing a significant digital transformation with increased adoption of AI and machine learning technologies for predictive maintenance, reservoir optimization, and operational efficiency. Companies are investing heavily in data analytics infrastructure to reduce operational costs and improve decision-making processes. There is a growing emphasis on ESG (Environmental, Social, and Governance) reporting and sustainability metrics in the energy sector, driving demand for data professionals who can develop analytics solutions for environmental monitoring and carbon footprint reduction. The integration of IoT sensors and real-time data streaming technologies in oil and gas operations is creating massive datasets that require advanced analytics capabilities, leading to increased demand for senior data engineers with domain expertise. Energy companies are increasingly adopting cloud-based analytics platforms like Databricks and Azure to handle large-scale data processing and machine learning workloads, requiring professionals with both technical expertise and industry knowledge.

Role Significance

The role reports to a Supervisor of Advanced Analytics, suggesting a team structure of 3-8 data professionals. As a senior member, this position likely involves mentoring junior team members and leading complex analytical projects while collaborating with a broader network of business stakeholders.
This is a senior-level individual contributor role with significant strategic impact. The position requires 7+ years of experience and involves developing solutions that inform strategic decision-making across all facets of the business. The role has high visibility with executive leadership and cross-functional collaboration requirements.

Key Projects

Development of predictive maintenance models for drilling and completion equipment to reduce downtime and operational costs Creation of reservoir performance optimization algorithms using geological and production data Implementation of real-time monitoring dashboards for environmental compliance and ESG reporting Design of supply chain and logistics optimization models for condensate and natural gas distribution Development of financial risk assessment models for commodity price forecasting and hedging strategies

Success Factors

Deep understanding of oil and gas operations combined with advanced data science skills to bridge the gap between technical capabilities and business needs Ability to work with complex, multi-source datasets from drilling operations, geological surveys, and production facilities while maintaining data quality and integrity Strong stakeholder management skills to collaborate effectively with diverse teams including engineers, geoscientists, and business leaders who may have varying levels of technical expertise Proficiency in translating complex analytical findings into actionable business insights that can drive strategic decision-making and operational improvements Continuous learning mindset to stay current with rapidly evolving AI/ML technologies and their applications in the energy sector

Market Demand

High demand. The intersection of data science expertise and oil and gas industry knowledge creates a specialized skill set that is highly sought after. The digital transformation of the energy sector, combined with the need for operational efficiency and ESG compliance, is driving strong demand for senior data analytics professionals.

Important Skills

Critical Skills

Python and SQL programming skills are essential for data manipulation, analysis, and model development in the company's cloud-based analytics environment. These languages form the foundation for most data science workflows and are required for effective collaboration with the existing technical team. Machine learning model development and deployment experience is crucial for creating predictive analytics solutions that optimize operational performance and reduce costs. The ability to work with regression, classification, time series, and deep learning models directly impacts business outcomes. Cloud platform proficiency, particularly with Databricks and Azure, is critical for working with the company's existing infrastructure and handling large-scale data processing requirements typical in oil and gas operations. Strong communication skills are vital for translating complex technical findings into actionable business insights for non-technical stakeholders across multiple departments, ensuring successful adoption of analytical solutions.

Beneficial Skills

Oil and gas industry experience provides valuable domain knowledge for understanding operational challenges and developing more effective analytical solutions tailored to energy sector requirements Experience with real-time data streaming and IoT technologies enhances the ability to work with sensor data from drilling and production operations MLOps and model deployment experience facilitates the transition from prototype to production-ready solutions in enterprise environments Agile methodology experience supports effective collaboration and rapid iteration in cross-functional project environments

Unique Aspects

Opportunity to work with cutting-edge infrastructure including Databricks, Github Copilot, and Azure IoT technologies in a traditional energy sector environment
Direct impact on strategic decision-making across multiple business functions including Engineering, Drilling, Completions, Geosciences, Marketing, and Environmental operations
Combination of traditional oil and gas domain expertise with modern data science and machine learning applications
Focus on responsible energy production with emphasis on ESG metrics and environmental sustainability analytics
Access to unique datasets from condensate and natural gas operations that provide distinctive analytical challenges and opportunities

Career Growth

Career progression typically occurs within 3-5 years for advancement to management roles, or 2-3 years for senior individual contributor positions. The specialized nature of oil and gas analytics experience accelerates career growth opportunities within the energy sector.

Potential Next Roles

Senior Data Science Manager or Analytics Team Lead positions overseeing multiple data professionals and strategic analytics initiatives Principal Data Scientist roles focusing on advanced research and development of cutting-edge analytics solutions Business Intelligence Director positions combining technical expertise with strategic business planning Chief Data Officer or VP of Analytics roles in mid-sized energy companies Consulting roles specializing in energy sector digital transformation and analytics implementation

Company Overview

ARC Resources Ltd.

ARC Resources Ltd. is a prominent Canadian energy company and the largest pure-play Montney producer, ranking as Canada's third-largest natural gas producer and largest condensate producer. The company has demonstrated strong operational and financial performance with a focus on low-cost, reliable energy production in the evolving global energy landscape.

ARC holds a strong market position as a leading independent oil and gas producer in Canada with significant presence in the Montney formation. The company's focus on operational excellence and financial performance has established it as a key player in the Canadian energy sector with a reputation for innovation and efficiency.
Based in Calgary, Alberta, ARC operates in Canada's energy capital with access to top-tier talent and industry expertise. The company's location provides strategic advantages for accessing skilled professionals and maintaining strong relationships with service providers and industry partners throughout Western Canada.
ARC emphasizes a high-performance culture with a strong commitment to diversity, inclusion, and operational excellence. The company promotes innovation, teamwork, and professional development while maintaining a long-term strategic view and focus on employee well-being and community impact.
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