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Intermediate Data Analyst to develop data systems utilizing Databricks, SQL and Python, and to assist reporting

Job in Calgary, Alberta, T3S, Canada
Listing for: S.i. Systems
Contract position
Listed on 2026-01-13
Job specializations:
  • IT/Tech
    Data Engineer, Data Analyst, Data Science Manager, Data Warehousing
Job Description & How to Apply Below
Position: Intermediate Data Analyst to develop data systems utilizing Databricks, SQL and Python, and to assist with reporting

Our Oil and Gas Client is seeking a Intermediate Data Analyst to develop data systems utilizing Databricks, SQL and Python, and to assist with reporting using Power BI

Calgary-based office (Downtown), Candidates will be in-office 5 days/week.

Must haves:

  • 5+ years of experience as a Data Analyst with experience in Data Modeling and reporting (
    Databricks
    , Python, SQL and Power BI
    )
  • Experience with Process and Production Data systems (
    PI AF, PVR
    ) and operational systems (
    SAP, Salesforce
    )
  • Understanding of the Oil and Gas industry (SCADA, Field Data Capture)
  • Nice to haves:

  • Ability to clearly and effectively communicate complex information, including visualizations and reports to diverse audiences.
  • Strong problem-solving, critical thinking, and analytical abilities.
  • Ability to work effectively with cross-functional teams.
  • Responsibilities:

  • Data Collection and Management (ETL):
  • Gathering data from various sources, including databases, systems, and potentially external sources.
  • Developing and maintaining data collection and storage systems.
  • Ensuring data accuracy, consistency, and quality.
  • Data Analysis and Interpretation:
  • Applying statistical techniques and tools to analyze data.
  • Identifying trends, patterns, and correlations within the data.
  • Developing data models to support analysis and predictions.
  • Creating visualizations, reports, and dashboards to present findings.
  • Communicating insights and recommendations to technical and non-technical audiences.
  • Collaborating with stakeholders to understand their needs and translate them into data-driven solutions.
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