Data Engineer

Job Overview The mission of the Data Analytics Engineer at Warwick Energy is to bridge the gap between data engineering and business intelligence (BI) teams seamlessly. In this role, you will convert raw data into well-structured, accessible datasets and design scalable data models that enable meaningful analytics and reporting. A critical part of this role involves applying data engineering principles to build and maintain trusted, high-quality data objects within the data warehouse. By ensuring the accuracy, consistency, and reliability of these data assets, you will create a strong foundation for scalable analytics and BI solutions. Your work will enable the organization to leverage a single source of truth for decision-making, fostering confidence in data-driven insights. As a detail-oriented professional, you will ensure high levels of accuracy and thoroughness in data preparation and documentation. Your problem-solving skills will be essential as you apply analytical thinking to tackle complex challenges in data workflows and in shaping the data. Collaboration is key in this role, as you will communicate effectively across teams and foster a cooperative working environment. An eagerness for continuous improvement will drive you to learn and implement efficient data solutions and creating robust data products that power BI applications, we encourage you to join our team. Key Job Responsibilities Data Transformation: Bridge data engineering and BI teams to convert raw data into structured, actionable datasets. Data Modeling: Design scalable data models and semantic layers to optimize BI tool analysis. Strengthen Data Infrastructure: Collaborate with data engineers to design and maintain robust data models for BI projects. Workflow Development: Develop and maintain version-controlled analytics workflows using tools like DBT. Business Alignment: Ensure analytical outputs meet business objectives and are accessible to all users. Technical Documentation: Create clear documentation for data models, workflows, and analytics solutions for both technical and non-technical stakeholders. Collaboration: Work with cross-functional teams to support data-driven decision-making and promote best practices in data analytics. Qualifications REQUIRED SKILLS Oil and Gas Industry Experience: At least 5 years of hands-on experience in various aspects of the oil and gas industry, understanding its unique data challenges. SQL Expertise: Proficient in writing complex SQL queries and designing data models that integrate diverse datasets. Experience with CTEs, advanced formulas, and windowing functions for sophisticated data transformations. Documentation Skills: Capable of producing clear and detailed documentation for data models, workflows, ELT processes, and analytics solutions to support team collaboration. Data Modeling Principles: Deep knowledge of data modeling concepts and best practices, including creating semantic layers for BI tools. BI Tools Experience: At least 5 years of experience in building data models for BI tools like Power BI and Spotfire, understanding data ingestion and transformation for optimal data display. Collaborative Experience: Proven ability to work effectively with functional business teams, data engineering teams, and analytics teams to align data solutions with business needs. Scalable Workflows: Proven ability to design and implement scalable workflows and optimize data queries for performance and efficiency. Version Control Knowledge: Familiar with using version control systems like Git and Azure DevOps to manage and track changes in data models and scripts. Desired Skills Snowflake and Microsoft Fabric: Proficient in using Snowflake and Microsoft Fabric for data warehousing and management. Cloud Platforms: Knowledgeable about cloud platforms like Snowflake, Azure, AWS, and GCP for data storage, processing, and analytics. Python for Data Manipulation: Competent in using Python for data manipulation, analysis, and automation tasks. Data Governance: Well-versed in data governance principles and compliance requirements, ensuring data quality and security. Required Skills Oil and Gas Industry Experience: At least 5 years of hands-on experience in various aspects of the oil and gas industry, understanding its unique data challenges. SQL Expertise: Proficient in writing complex SQL queries and designing data models that integrate diverse datasets. Experience with CTEs, advanced formulas, and windowing functions for sophisticated data transformations. Documentation Skills: Capable of producing clear and detailed documentation for data models, workflows, ELT processes, and analytics solutions to support team collaboration. Data Modeling Principles: Deep knowledge of data modeling concepts and best practices, including creating semantic layers for BI tools. BI Tools Experience: At least 5 years of experience in building data models for BI tools like Power BI and Spotfire, understanding data ingestion and transformation for optimal data display. Collaborative Experience: Proven ability to work effectively with functional business teams, data engineering teams, and analytics teams to align data solutions with business needs. Scalable Workflows: Proven ability to design and implement scalable workflows and optimize data queries for performance and efficiency. Version Control Knowledge: Familiar with using version control systems like Git and Azure DevOps to manage and track changes in data models and scripts. DESIRED SKILLS Snowflake and Microsoft Fabric: Proficient in using Snowflake and Microsoft Fabric for data warehousing and management. Cloud Platforms: Knowledgeable about cloud platforms like Snowflake, Azure, AWS, and GCP for data storage, processing, and analytics. Python for Data Manipulation: Competent in using Python for data manipulation, analysis, and automation tasks. Data Governance: Well-versed in data governance principles and compliance requirements, ensuring data quality and security. #J-18808-Ljbffr