About the position:

A Data Analyst is responsible for gathering, analyzing and problem solving as it relates to data, types of data, and relationships among data elements within a business system or IT system and with business domain expertise. A Data Analyst provides expertise on how Business workflows map to data, and how data can be integrated to build reusable data products. A Data analyst will serve as a subject matter expert for delivery teams.
The Data Analyst will support the analysis and visualization of data to provide valuable insights that drive business decisions. This role requires a strong understanding of data processing, reporting, and visualization tools, as well as a good working knowledge of Microsoft Azure Services and Power Platform. The ideal candidate will have hands-on experience with data modeling, creating dashboards, and leveraging cloud technologies for data management.

Key responsibilities:

• Analyze data to extract meaningful insights, trends, and patterns that can support decision-making across the organization.
• Develop and maintain dashboards and visualizations using Power BI, Spotfire, and Tableau to present data insights in an easy-to-understand format for stakeholders.
• Work with Azure Synapse Analytics, Azure Data Lake, and Azure SQL Database to store, transform, and retrieve data efficiently.
• Assist in data preparation, cleaning, and integration activities for analysis, ensuring high data quality.
• Collaborate with data engineers, business stakeholders, and IT teams to understand data requirements and contribute to the delivery of data-driven solutions.
• Leverage Power Platform tools to automate tasks, create workflows, and enhance data analysis processes.
• Provide support for ongoing analysis and maintain documentation for data processes, reports, and dashboards.

Required Qualifications:

• Experience: Overall 2-4 years of experience with 2 years of proven experience in data analysis, data visualization, or related fields.
• Bachelor’s degree in Data Analytics, Computer Science, Statistics, or a related field (or equivalent experience).
0-5 years experience

Technical Skills:

• Proficiency in Microsoft Azure services, including Azure Synapse Analytics, Azure Data Lake, and Azure SQL Database.
• Experience in data visualization tools such as Power BI, Spotfire, and Tableau.
• Strong skills in data manipulation and transformation using SQL.
• Familiarity with the Microsoft Power Platform, including Power Apps, Power Automate, and Power BI.
• Proficiency in data visualization tools such as Power BI, Spotfire, Tableau.Data modeling techniques, data fluency and governance.
• Proficiency in Oil & gas workflows and data types
• Data Analysis: Understanding of data analysis concepts and experience in data modeling and building insightful reports.
• Problem Solving: Strong analytical and problem-solving skills, with attention to detail.
• Communication Skills: Ability to communicate complex data findings in a clear and concise manner to non-technical stakeholders.
• • Team Collaboration: Ability to work effectively as part of a team, sharing knowledge, and supporting other team members.
• Excellent communication and collaboration skills with demonstrated ability to build trusted working relationships with remote peers and stakeholders (internal & external parties) across global teams and time zones.
• Strong knowledge of Microsoft Azure Services & Power Platform, including Azure Synapse Analytics, Azure Data Lake, and Azure SQL Database.
• Experience with SQL and data querying languages.
• Experience with Python for data wrangling.
• Strong analytical and problem-solving skills with attention to detail and accuracy
• Fundamental knowledge of Information Risk Management (IRM).

Preferred Qualifications:

• Microsoft Power BI Data Analyst certification (PL-300)
• Ability to discover and prepare datasets into clean, understandable, usable, datasets for data analysis.
• Cloud Certifications: Certifications in Microsoft Azure (e.g., Azure Data Fundamentals, Azure Data Engineer Associate) are preferred.
• Experience with ETL Tools: Exposure to ETL tools and data integration techniques.
• Advanced Analytics: Experience or knowledge of machine learning or advanced analytics is a plus.
• Scripting Languages: Basic understanding of scripting languages such as Python or R for data analysis.