Data Analytics Analyst 2

Data Analyst II

Birmingham, AL

Hybrid role

$55 per hour

ABOUT THE ROLE

Our client is seeking a Data Analyst II to join their team in Birmingham, AL, in a hybrid work environment. As a Data Analyst II, you will play a key role in supporting enterprise reporting, dashboards, and analytics products by working with large, complex datasets in cloud-based environments. You will be responsible for troubleshooting data quality and pipeline issues, preparing data optimized for analysis and visualization, and ensuring data accuracy and reliability. The ideal candidate will have 3-5 years of experience in data analytics or business intelligence, strong technical skills in SQL, data modeling, and cloud data platforms, and the ability to translate business questions into actionable analytical datasets. Experience in utilities, energy, or regulated industries, and familiarity with geospatial data, ETL/ELT pipelines, and data governance are highly valued. You will collaborate with cross-functional teams, communicate findings to both technical and non-technical stakeholders, and contribute to the continuous improvement of data processes and products.

WHAT YOU'LL DO

• Analyze and interpret large, complex datasets in a cloud-based environment
• Develop, optimize, and maintain data models and transformation pipelines for analytics and visualization
• Write, document, and optimize SQL queries for data extraction and reporting, ensuring code handles edge cases and errors gracefully
• Support enterprise reporting, dashboards, and analytics products using BI tools such as Power BI and Tableau
• Troubleshoot and resolve data quality, pipeline, and ingestion issues, coordinating with cross-functional teams
• Validate data accuracy, identify discrepancies between source and cloud datasets, and facilitate root-cause analysis and resolution
• Create charts and graphs using Python plotting libraries and optimize visualization performance for large datasets (e.g., data binning, downsampling, efficient plotting methods)
• Collaborate with data engineers and subject matter experts to translate business questions into efficient analytical datasets
• Prioritize and manage multiple data requests and investigations simultaneously
• Document processes, maintain version control (e.g., Git), and ensure data governance, lineage, and metadata management
• Apply statistical methods (e.g., correlation, trend analysis, least-squares fitting) and geospatial analysis as needed for domain-specific projects
• Work with geospatial data, including GeoTIFFs and spatial indices, and optimize performance for geospatial analytics
• Communicate findings and data issues clearly to both technical and non-technical stakeholders, providing actionable insights
• Contribute to the continuous improvement of ETL/ELT pipelines and orchestration processes
• Work with operational, asset, or time-series data, including imperfect or operational source systems

WHAT YOU BRING

• 3-5 years of professional experience in data analytics, business intelligence, or related roles
• Proven experience with large, complex datasets in cloud-based environments
• Experience supporting enterprise reporting, dashboards, and analytics products
• Demonstrated troubleshooting skills for data quality, pipeline, or ingestion issues
• Strong data modeling and transformation abilities for analysis and visualization, including preparing data for dashboard consumption
• Ability to write robust, reusable, and well-documented SQL queries (joins, CTEs, window functions, performance optimization)
• Hands-on experience with cloud data platforms such as Databricks, Azure Synapse, Snowflake, or BigQuery
• Understanding of data movement from source systems into cloud storage and analytics layers
• Ability to identify and resolve data discrepancies between source and cloud datasets, and facilitate root-cause analysis across teams
• Strong understanding of how data structure impacts visualization performance and usability
• Familiarity with resolving visualization bottlenecks for large datasets (e.g., data binning, downsampling, efficient plotting methods)
• Experience using Python plotting libraries for charts and graphs
• Experience with BI tools such as Power BI or Tableau
• Strong analytical and problem-solving skills
• Ability to work independently and collaborate with data engineers and subject matter experts
• Clear written and verbal communication skills, especially when explaining data issues or findings
• Experience prioritizing multiple data requests and investigations
• Preferred: Background in Atmospheric Science or Earth Science
• Preferred: Experience with PySpark or Python for data analysis and transformations
• Preferred: Experience with geospatial data, GeoTIFFs, and spatial indices
• Knowledge of basic statistical concepts and trend analysis (e.g., correlation, least-squares fitting)
• Familiarity with multithreading or multiprocessing for large datasets
• Familiarity with ETL/ELT pipelines and orchestration
• Experience with version control (e.g., Git)
• Basic understanding of data governance, lineage, or metadata management
• 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