Digital Data Support Engineer

Role: Digital Data Support Engineer

Location: Remote (EST/CST)

Job Description:

Perform complex analytical and statistical modeling on large data sets to support various business operations and organizational objectives.

Define data requirements, perform data collection, processing, cleaning, analysis, modeling and visualization.

Identify data patterns and trends to answer business questions and improve decision making.

Identify opportunities to increase efficiency and automation of data analysis processes and procedures.

Leads the most complex data analysis with minimal supervision and wide latitude for independent judgment.

Individual contributor and mentor to more junior staff.

Design, develop, maintain, and manage highly advanced reporting, dashboards, data models and analytical results of significant impact.

Evaluate and define functional requirements for analytics and business intelligence (BI) solutions

Retrieve, analyze and validate data and test accuracy of reported results.

Work directly with project leads to understand requirements and propose key analytics solutions to drive effective decision-making and influence business objectives.

Produce actionable reports that demonstrate key performance indicators, identify areas of improvement for current operations, and show root cause analysis of problems.

Analyze and summarize business operations, customer and/or economic data in order to improve business intelligence, optimize operating effectiveness and predict business outcomes.

Identify trends and patterns in business data; create data visualizations to support business decision making.

Build new and/or modify existing database/data warehouse/data mart and business intelligence solutions to meet business and system requirements.

Collaborate with business units and senior management to conduct needs assessment to support business unit objectives.

Provides input on highly complex Data Science and Big Data projects.

Effectively communicate findings and insight to stakeholders and provide business strategy recommendations for optimizing business performance.

Lead, guide, and mentor less experienced staff; Direct the work of others as needed.

Perform other duties as assigned.

Qualifications:

Master's degree in a related field or equivalent experience.

Advanced statistical, mathematical, forecasting, and analytical skills, including root-cause analysis and problem resolution.

Expertise in interpreting, analyzing, and modeling data to identify trends, risks, and opportunities.

Strong ability to research, compile, document, and present data, processes, and findings clearly and concisely.

Expert knowledge of ETL processes, data sourcing, cleansing, warehousing, pipelines, and data structures.

Proficient in data modeling, design tools, requirements analysis, and statistical programming/query languages (e.g., SQL, PySpark, Power BI).

Skilled in applying statistical methods, including descriptive statistics, correlation, regression, and predictive modeling.

Experienced in transforming data into meaningful insights, visualizations, and decision-ready outputs.

Advanced proficiency with database, presentation, word processing, and spreadsheet software.