Data Engineer & Analytics Developer

Freese and Nichols • Raleigh, NC

1d • Hybrid

About The Position

FNI is seeking a hands-on Data Engineer & Analytics Developer to transform complex, inconsistent, and disparate data into trusted, analysis-ready information, meaningful insights, and working analytical tools. The role focuses primarily on data engineering: accessing and assessing source data, building repeatable ETL/ELT processes, improving data quality, and producing reliable data models and outputs. It also includes conducting analysis and building interactive dashboards, reports, and geospatial or other data-driven tools.

The successful candidate will apply strong data management practices so that data, code, transformations, metadata, and analytical outputs are organized, documented, traceable, and maintainable. The position works with a business analyst / visualization lead who guides client discovery, translates user requirements, and directs the overall user experience and visualization approach. The Data Engineer & Analytics Developer carries out the technical work of engineering and analyzing data and implementing and refining visualization deliverables under that guidance.

The role collaborates with FNI engineers, scientists, project managers, and other technical staff to deliver reliable, maintainable solutions and meaningful insights. Freese and Nichols has a flexible hybrid work environment, with up to 40% remote work. The company describes its culture through LEADS values: Learn continuously, Engage as family, Act with integrity, Deliver quality, and Serve always.

Requirements

• Bachelor's degree in Computer Science, Information Systems, Data Science, Engineering, Geography, or a related field.
• At least five years of professional experience in data engineering, data analytics, business intelligence, or a related discipline, including substantial hands-on data engineering responsibility.
• Demonstrated success taking raw or poorly structured data through ingestion, ETL/ELT, cleaning, validation, transformation, and modeling to produce reliable analytical outputs; experience building processes rather than solely consuming prepared datasets.
• Strong SQL skills, including joins, complex queries, and relational data modeling.
• Proficiency with Python or another scripting/programming language used for data processing and automation.
• Ability to integrate and reconcile information from multiple data sources, identify data-quality problems, and document reproducible solutions.
• Ability to perform analysis, assess the credibility of results, and explain what the data means in the context of a real-world problem.
• Experience developing interactive analytical tools or dashboards in at least one enterprise-grade platform such as Microsoft Power BI, Tableau, or Esri GIS / Experience Builder.
• Ability to work from technical requirements and UI/UX direction to implement a complete, functional deliverable, including testing and iterative improvement.
• Working knowledge of version control practices for managing code, scripts, configurations, and other technical assets in a collaborative environment.
• Effective communication, collaboration, and time-management skills across concurrent assignments.

Nice To Haves

• Experience with cloud data services or platforms such as Microsoft Azure, AWS, or Google Cloud, and scheduled or orchestrated data-processing workflows.
• Experience with advanced Power BI data modeling, DAX, Power Query (M), Tableau development, or comparable BI-platform capabilities.
• Experience with geospatial data integration, GIS analysis, and Esri applications.
• Familiarity with environmental, municipal, infrastructure, or public-sector data.
• Additional skills in R, Python, JavaScript, statistical analysis, or other analytical and application-development methods.
• Knowledge of iterative or Agile delivery practices and relevant certifications, such as Microsoft PL-300, Tableau, or Esri credentials.
• Experience with modern data processing, query, and analytical technologies beyond traditional relational databases, such as DuckDB, Spark, Polars, or similar tools.

Responsibilities

• Investigate and profile source data from databases, spreadsheets, APIs, GIS datasets, files, and cloud-based systems, identifying access, structure, quality, and integration challenges.
• Design, build, document, and maintain repeatable ETL/ELT pipelines to extract, combine, clean, standardize, and transform data from disparate sources.
• Write and optimize SQL queries and use programming or scripting to automate data preparation, transformation, validation, and recurring workflows.
• Develop and maintain logical data models, schemas, and structured datasets for analysis, reporting, dashboards, and geospatial applications.
• Implement data-quality checks, reconciliation, and exception handling for missing, duplicated, inconsistent, or erroneous records, and verify results with project subject matter experts.
• Troubleshoot data issues, improve reliability and performance, and document source-to-output transformations, assumptions, and dependencies.
• Evaluate technical feasibility, dependencies, and implementation effort, and provide practical data-engineering solutions in coordination with project and business analysis leads.
• Apply data management practices throughout the data lifecycle, including consistent naming and organization, metadata standards, data dictionaries, source and transformation documentation, lineage, and documentation of assumptions, limitations, and intended uses.
• Use version control to manage code, scripts, configurations, and other technical assets so analytical workflows are traceable, reproducible, and maintainable.
• Perform exploratory and quantitative analysis to identify patterns, trends, anomalies, relationships, and findings that address project questions.
• Apply knowledge of data provenance, domain context, and analytical limitations to distinguish meaningful insights from misleading or incomplete results.
• Develop analysis-ready datasets, calculations, summaries, and clean outputs that support decision-making and downstream applications.
• Work with technical experts and the business analyst / visualization lead to interpret results, validate conclusions, and explain the significance and practical implications of findings.
• Build, configure, test, and deploy interactive dashboards, analytical reports, and data-driven tools using platforms such as Power BI, Tableau, Excel, and Esri GIS applications, as project needs dictate.
• Implement visualization direction for page layouts, charts, map displays, filters, navigation, labeling, user interactions, and other UI/UX elements, refining products through iterative review.
• Connect visualization products to reliable datasets and implement the calculations, data relationships, and refresh processes needed for accurate, maintainable tools.
• Test analytical results, dashboard behavior, usability, and performance; correct defects and enhance deployed products as data and user needs evolve.
• Translate documented requirements and visualization direction into technical tasks and working deliverables, raising feasibility, data-quality, scope, and implementation concerns early.
• Coordinate with FNI engineers, scientists, project managers, and other technical staff to validate data and deliver solutions suited to the client's operating context.
• Communicate technical progress, analytical findings, and implementation options clearly to technical and non-technical team members.
• Prepare maintainable documentation and handoffs, contribute reusable code, data processes, and templates, and provide technical input to scoping and proposal efforts.

Benefits

• Comprehensive benefits package.
• Paid overtime for salaried employees.
• Annual bonus.
• Access to company cabins in Red River, New Mexico, and Banner Elk, North Carolina.
• Flexible hybrid work environment, including up to 40% remote work.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level