Norway
Experienced data engineer and analytics professional with a strong track record in delivering robust solutions. Holding Bachelor's degree in Petroleum Engineering and Master's degree in Data Science. Deep understanding of the petroleum engineering domain, specializing in reservoir characterization, drilling engineering, and production optimization, I possess a comprehensive understanding of the complexities within the petroleum sector, bridging the gap between traditional engineering practices and modern data-driven methodologies. My Master's degree equipped with advanced skills in statistical analysis, machine learning, and data visualization. My work experience has allowed me to grasp the unique requirements and intricacies of the industry and by leveraging these skills, I have implemented cutting-edge data analytics techniques to extract valuable insights from complex datasets. This has empowered organizations to make data-driven decisions and drive business growth. I am committed to continuous learning and actively participate in professional networks to stay up-to-date with emerging technologies and industry trends. My results-oriented mindset and dedication to driving business success through effective data utilization set me apart.
TDI CC Data Engineering & Platform • Lead the design and development of efficient data ingestion pipelines, maximizing the value of seismic and subsurface data assets within Microsoft Azure environments. • Actively involved in the platform team, developing and maintaining solutions related to subsurface data management and ensuring accurate and timely availability of well and seismic project data for end users. • Gain in-depth understanding of seismic data handling, focusing on the management and processing of prestack and poststack data, ensuring accurate seismic geometry conversion and effective horizon interpretation for enhanced subsurface analysis. • Provide comprehensive data loading and ETL services, enabling effective data integration and accessibility for customers while cultivating a passion for cloud-based solutions. • Develop secure solutions using REST APIs, demonstrating proficiency in Python and C# to enhance system functionalities. • Implement Agile practices and automation for continuous integration and deployment, while enhancing and developing new tools and APIs for Change Data Capture (CDC). • Participate in code reviews and collaborate with developers to ensure high-quality code that adheres to best practices and secure coding standards. • Engage in the full software development lifecycle, from planning and prioritizing requirements to deployment and maintenance, while designing, developing, and maintaining software applications for data ingestion into the subsurface data management platform (OSDU).
• Liaise with relevant business department to help gather technical and non-technical business demand requirements • Create the business demand specification work products or deliverable • Identify potential continuous improvement opportunities focusing on quality outcome desired and risk associated to business • Gather requirements, perform requirements analysis, and perform IT solution assessment and validation using the right tools available • Assist the execution of business demand (on demand) • Track and monitor change progress and escalate issues to appropriate stakeholders • Continually identify, prioritize and mitigate project risks • Work together with Enterprise Architect(s) on new application and infrastructure technology to ensure alignment of business demand against overall technology landscape • Transform business requirements into functionally useful business intelligence solutions utilizing the Microsoft PowerBI Platform • Build reporting models, visual reports, dashboards and KPI scorecards using Power BI desktop • Implement row level security (RLS) on data and have an understanding of application security model in Power BI • Generate advance level calculations on data set by using Power query, M programming, Python and R programming
• Support implementation of projects focused on collecting, aggregating, storing, reconciling and ingesting data from disparate sources to enable analysis and decision making. • Ensuring business user and stakeholders able to access and manipulate data (Hive table) for routine and ad hoc analysis. • Support full lifecycle of data ingestion through analytics to action. • Support planning and delivery of PPG Datalake and storage architecture. • Support ,enhance and test ingestion workflow in Beta environment by leveraging Talend Studio (Develop, Test & Debug production issue). • Develop and maintain data ingestion schematics, layouts, frameworks and databases for data storage and analytics. • Deliver data to end users using PowerBI report and visualization tool. • Customize data ingestion workflow, storage and metadata for unique source system. • Implement effective metrics and monitoring process. • Participate in data integration, design and development of business intelligence reports. • Program and maintain metadata and data structure as per end user requests. • Customize scala application in Maven project using Scala IDE (IntelliJ & Eclipse). • Involve in data ingestion mapping ad movement across environment by using Azure Data Factory. • Familiar with ETL tools (Talend Studio 6.3, 7.1 & SAP Data Services), Microsoft Azure, DevOps, Databricks, Sqoop, MapReduce, ADF, Batch Processing, SQL server, Oracle, Pervasive, Hive, Spark, Scala, YARN,
• Developed practical knowledge in distributed computing, big data and Hadoop environment. • Played an active role in developing the data lake environment at PPG. • Actively designs, codes, tests, and debugs SQL queries in data lake development project. Tech: Office 365, Microsoft Azure, Talend, Qlikview, PowerBI, DevOps, Microsoft Data Services (MDS), Hadoop, Hive, Scala for Spark, SQL server, SQL, YARN, Sqoop.
• Set-up and run analysis using R programming. • Analyses communicate and visualize findings on the data. • Understand importance of data management and realise the value from an organisation’s data. • Develop predictive models and monitor model output. Tech: SQL, NoSQL, Python, R programming, Hadoop, Tableau.