Data Analytics Analyst

About the Role

Key Responsibilities

• Design, develop, and maintain scalable data pipelines and architectures to support analytics and reporting needs.
• Propose and implement advanced data ingestion, preparation, integration, and operationalization techniques.
• Analyze data sources to determine ETL strategies (full vs. incremental loads) and define necessary components for incremental loads.
• Build modern data solutions using Microsoft Fabric (Lakehouse, Warehouse, Notebooks, Data Pipelines).
• Organize data using the Medallion architecture (Bronze, Silver, Gold) to create valuable insights.
• Develop and implement data quality processes to validate, cleanse, and monitor data integrity throughout the pipeline.
• Troubleshoot data issues proactively, ensuring timely resolution of inconsistencies or performance bottlenecks.
• Optimize database performance and recommend improvements for query execution and data storage.
• Automate workflows and data processes using Power Automate to improve operational efficiency.
• Drive automation and improve data usability and governance through effective metadata management.
• Prepare data for AI-driven predictive and prescriptive analytics, ensuring it is structured, transformed, and optimized for machine learning models and advanced analytical techniques.
• Collaborate with cross-functional teams to translate business requirements into effective data models and schemas.
• Develop data models (Star Schema, ER diagrams) to support data warehousing solutions.
• Develop and maintain Power BI semantic models that are reusable, optimized for performance, and designed for self-service analytics.
• Stay up to date with emerging technologies, best practices, and industry trends.
• Other duties assigned

Requirements

• Bachelor's degree in computer science, information systems, or related field.
• 5+ years of experience in developing data pipelines, ETL processes, or other data engineering-related functions.
• 3+ years of experience working in cross-functional teams and collaborating with business stakeholders.
• Extensive experience designing, developing, and maintaining scalable data pipelines optimized for data movement, transformation, and storage.
• Strong troubleshooting skills to identify, diagnose, and resolve data quality and performance issues.
• Proficient in analyzing and optimizing database performance, understanding how design decisions affect system efficiency.
• Experience in preparing data for AI and machine learning applications, including feature engineering, data normalization, and statistical transformations (strongly preferred).
• Strong knowledge of data modeling techniques, including Star Schema and ER diagrams.
• Experience developing semantic models and reports in Microsoft Power BI or other reporting tools (a plus).
• Highly skilled in writing SQL queries and optimizing complex queries across large datasets.
• Hands-on experience with SQL Server and/or Oracle databases.
• Experience extracting data from SaaS applications (e.g., Oracle ERP Cloud, UKG) using REST API, SOAP Services, or CSV/Excel Exports.
• Ability to work across multiple deployment environments including cloud, on-premises, and hybrid.
• Excellent problem-solving skills, with the ability to research information and work independently.
• Strong communication and collaboration skills, capable of working effectively with both technical and non-technical stakeholders.
• Strong analytical skills with attention to detail and accuracy.
• Knowledge or familiarity with the midstream services industry and data related to natural gas, NGLs, and crude oil is strongly preferred.
• Familiarity with Master Data Management (MDM) solutions is a plus.
• Regular and reliable attendance