Focus on using ETL best practices on data to solve business problems and improve efficiency within our organization's IT systems. Collect, clean and interpret data to identify trends and actionable insights, then communicate these findings to stakeholders to inform decision-making and drive data and process improvements. Develop data models, align data architecture with business objectives and technological capabilities.

Key Responsibilities:

• Data Collection and Management:

• Gathering data from various sources, including databases, systems, and potentially external sources.

• Developing and maintaining data collection and storage systems.

• Ensuring data accuracy, integrity, consistency, and quality.

• Data Analysis and Interpretation:

• Applying statistical techniques and tools to analyze data.

• Identifying trends, patterns, correlations and inconsistencies within the data and associated systems

• Developing data models to support analysis and predictions.

• Communication and Reporting:

• Creating visualizations, reports, and dashboards to present findings.

• Communicating insights and proposing recommendations to technical and non-technical audiences.

• Collaborating with stakeholders to understand their needs and translate them into data-driven solutions.

• Troubleshooting and Optimization:

• Identifying and resolving issues with data systems and processes.

• Optimizing data collection, storage, and analysis processes.

• Continuously improving data quality and efficiency, and creating low maintenance solutions.

• Designing and Implementing Data Models:

• Determining how data is stored, accessed, and managed to achieve business goals.

• Ensuring Data Integrity and Security:

• Contributing to standards for data quality, security, and compliance.

• Developing Data Strategies:

• Contributing to the overall data strategy and ensuring it aligns with business goals.

• Staying Current with Technology:

• Continuously researching and evaluating new technologies and trends in data management.

Required Skills:

• Technical Skills: Proficiency in SQL, data modeling and database design principles, and Power BI.

• Analytical Skills: Strong problem-solving, critical thinking, and analytical abilities.

• Collaboration Skills: Ability to work effectively with cross-functional teams including IT, operations, engineering, and finance.

Desirable Skills:

• Technical Skills: Proficiency in Python specifically (but any statistical programming language is a plus) Databricks. PI Data Historian, MS SQL Server. other data visualization tools, and REST API programming, data migration. Proficiency in data warehousing, ETL (extract, transform, load) processes, and data modeling tools.

• Communication Skills: Ability to clearly and effectively communicate complex information, data flows and processes to diverse audiences.

• Domain Knowledge: Understanding of the upstream oil & gas industry, specifically Process Data, SCADA, Field Data Capture, heavy oil production processes, AB and SK air emissions regulations.