Data Analyst (Hybrid/Experience in Utilities/Energy/infrastructure/Regulated Industries)

Job Title : Data Analyst (Hybrid/Experience in utilities, energy, infrastructure, or regulated industries Job Description : Experience • 3-5 years of professional experience in data analytics, business intelligence, or a related role • Proven experience working with large, complex datasets in a cloud-based environment • Experience supporting enterprise reporting, dashboards, and analytics products • Demonstrated experience troubleshooting data quality, pipeline, or ingestion issues Technical Skills & Languages Data modeling & transformation • Ability to prepare data optimized for analysis, visualization, and dashboard consumption • Ability to write robust code that handles edge cases, implements retries, and fails gracefully under error conditions • SQL • Familiarity with joins, CTEs, window functions, performance optimization • Writing and maintaining reusable, well-documented queries • Cloud data platforms • Hands-on experience with Databricks, Azure Synapse, Snowflake, BigQuery, or similar • Understanding of how data moves from source systems into cloud storage and analytics layers • Data quality & validation • Ability to identify discrepancies between source systems and cloud datasets • Experience facilitating root-cause analysis and coordinating resolution across teams • Analytics & Visualization • Strong understanding of how data structure impacts visualization performance and usability • Familiarity with common bottlenecks when rendering large datasets and their resolution (e.g., data binning, down sampling, efficient plotting methods and memory use) • Experience using plotting libraries in a language like Python to create charts and graphs • Experience supporting dashboards and reports using tools such as: Power BI, Tableau, or similar enterprise BI platforms Soft Skills & Work Style • Strong analytical and problem-solving skills • Ability to work independently while collaborating with data engineers and internal SMEs • Clear written and verbal communication, especially when explaining data issues or findings • Experience prioritizing work across multiple data requests and investigations Preferred Qualifications • Background in Atmospheric Science or another Earth Science • Experience with data visualization (Power BI) is a plus - ??Experience PySpark or Python for data analysis and transformations • Experience working with GeoTIFFs or other raster datasets • Experience with geospatial data and performance optimizations when working with geospatial data such as leveraging spatial indices • Knowledge of basic statistical concepts like correlation and trend analysis using methods like least-squares fitting • Familiarity with the concepts of using multiple threads and/or multiple CPUs to process large datasets quickly • Familiarity with ETL / ELT pipelines and orchestration concepts • Experience with version control (Git or similar) • Basic understanding of data governance, lineage, or metadata management Domain & Business Experience • Experience in utilities, energy, infrastructure, or regulated industries • Familiarity with operational, asset, or time-series data • Experience working with imperfect or operational source systems • Ability to translate business questions into efficient analytical datasets • Demonstrated attention to detail with a strong focus on data accuracy and reliability