The primary focus is to apply advanced data analytics on operational data for Liquid Pipelines Assets. Focused effort will be on extracting insight from structured and unstructured data, and turning it into actionable results. The goal is to enable data based decisions, and drive them towards maximizing process safety, reliability, and throughput, while minimizing cost of operations and risk.
- Apply the first principles of engineering and analytics to provide guidance and insight for maximizing process safety, operational reliability, and throughput on the Liquid Pipelines network.
- Collect & validate data, extract insight, and build business cases to drive actions based on data and Subject Matter Experts' (SMEs) judgments.
- Use open source codes such as R, or Python to connect to SQL databases and mine large amounts of IT/OT data.
- Explore and describe data sets using statistical methods to estimate values, test hypotheses, and examine relationships between various operational parameters.
- Design strong visualizations using PI Vision, and Microsoft PowerBI to deliver insight to decision makers in the organization.
- Process and interpret large amounts of operational data from the field historians (OSISoft's PI) to challenge ideas, and apply inquisitive analytics to diagnose the problem.
- Act as a liaison between the team and external groups including IT to scale up solutions, and apply predictive / prescriptive analytics where applicable.
- Collaborate with various Stakeholders to pursue opportunities to increase reliability and throughput of the Liquids Pipeline assets.
- Lead department initiatives from conception to completion, follow the team's delivery model, and identify areas of improvements throughout the different phases of the project.
- Support process related incident investigations where required, to supplement historical data as part of the root cause analysis.
- Support the Instrumentations, Process Engineering, and Transient Hydraulic (iPETH) teams to ensure proper process information is used in all aspects of the project.
- Leverage project management skills to coordinate and execute solutions.
- Help identify enhancements to the engineering standards and specifications.
Knowledge, Skills & Abilities
- Completion of an undergraduate degree (or higher) in Engineering from a recognized post-secondary institution.
- Must be registered or qualified to register as a P.Eng. in the Province of Alberta (APEGA).
- Four (4) or more years of experience in engineering and data analytics.
- Demonstrated competence in engineering and data analytics; preferably within the oil & gas industry.
- Knowledge of pipeline and facility operations; exposure to risk based industries like oil & gas is considered an asset (industries like nuclear or aerospace for example).
- Strong understanding of the different layers of data analytics, and when they are applied.
- A good understanding of statistical analysis, interpreting data correlations through inference.
- Aptitude to work with large data sets to reveal patterns, trends, and correlations.
- Ability to extract meaningful information from unstructured data, and apply first principles of engineering.
- Experience in PI Historian, PI Process book (PI Vision), PI AF is considered an asset.
- Knowledge of a coding language preferably one of the following VBA, R, Python, and/or SAS is considered an asset.
- Holds strong interpersonal skills (self-motivated, and proactive), able to thrive in a dynamic work environment and meet deadlines.
- Well-developed problem solving, decision-making, organization and planning skills.
- Ability to manage multiple assignments while meeting established deadlines.
- Ability to effectively interact with peers, internal stakeholders, upper level management, vendors, and service providers.
- Growth mindset, ability to learn quickly & collaborate with various Stakeholders.
- Knowledge of relevant codes such as CSA Z662, ASME B31.3, Standards.
- Ability to legally work in Canada
- Ability to evaluate large data infused excel spreadsheets and replace with more streamlined tools would be considered an asset.
- Working knowledge of hydraulics and modelling software such as Stoner Pipeline Simulator, PipeFlow, Pipeline Studio, and/or AFT Fathom/Impulse would be considered an asset.
- Working knowledge of ESRI platform (EMaps) would be considered an asset.
- Familiarity with risk assessment methodologies such as What If, PHA, HAZOP, or LOPA.