Data Engineer & Analytics Developer

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 primary emphasis of this role is data engineering, accessing and assessing source data, building repeatable extract-transform-load (ETL/ELT) processes, improving data quality, and producing reliable data models and outputs. The role also conducts analysis and builds interactive dashboards, reports, and geospatial or other data-driven tools. The ideal candidate is detail-oriented and comfortable with in depth data exploration, bringing strong data management practices to their work to ensure data, code, transformations, metadata, and analytical outputs are organized, documented, traceable, and maintainable.

This position partners with a business analyst / visualization lead who guides client discovery, translates user requirements, and directs the overall user experience (UI/UX) and visualization approach. The Data Engineer & Analytics Developer is responsible for executing the technical work: engineering the data, analyzing it, and implementing and refining the visualization deliverables under that guidance. Successful candidates can work alongside the business analyst / visualization lead to go from raw data to a functioning end-user solution, applying sound technical and analytical judgment to produce reliable, maintainable outputs and meaningful insights.

Key Responsibilities

Data Engineering, Integration & Quality | Primary Focus

• •Investigate and profile source data, including databases, spreadsheets, APIs, GIS datasets, files, and cloud-based systems; identify access, structure, quality, and integration challenges.
• •Design, build, document, and maintain repeatable ETL/ELT pipelines that 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 suitable for analysis, reporting, dashboards, and geospatial applications.
• •Implement data-quality checks, reconciliation, and exception handling for missing, duplicated, inconsistent, or erroneous records; verify results with project subject matter experts.
• •Troubleshoot data issues, improve reliability and performance, and maintain clear documentation of source-to-output transformations, assumptions, and dependencies.
• •Evaluate technical feasibility, dependencies, and implementation effort and provide practical data-engineering solutions in coordination with the project and business analysis leads.
• •Apply sound data management practices throughout the data lifecycle, including consistent naming and organization, metadata standards and data dictionaries, documentation of data sources, transformations and lineage, identification of authoritative and derived datasets, and capture of important assumptions, limitations, and intended uses.
• •Use version control practices to manage code, scripts, configuration, and other technical assets so that analytical workflows are traceable, reproducible, and maintainable.

Data Analysis & Insight Development

• •Perform exploratory and quantitative analysis to identify patterns, trends, anomalies, relationships, and findings that address project questions.
• •Apply an understanding 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 help explain the significance and practical implications of findings.

Dashboard, Visualization & Analytical Tool Execution

• •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 the visualization lead's direction for page layouts, charts, map displays, filters, navigation, labeling, user interactions, and other UI/UX elements; refine the product through iterative review.
• •Connect visualization products to reliable datasets and implement calculations, data relationships, and refresh processes necessary for accurate, maintainable tools.
• •Test analytical results, dashboard behavior, usability, and performance; correct defects and enhance deployed products as data and user needs evolve.

Project Delivery & Collaboration

• •Translate documented requirements and visualization direction into technical tasks and working deliverables; raise 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 that fit the client's operating context.
• •Communicate technical progress, analytical findings, and implementation options clearly to both technical and non-technical team members.
• •Prepare maintainable documentation and handoffs; contribute reusable code, data processes, templates, and technical input to scoping and proposal efforts.

Qualifications

• •Bachelor's degree in Computer Science, Information Systems, Data Science, Engineering, Geography, or a related field.
• •At least five (5) 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, not 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.
• •Proven 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.

Preferred Qualifications

• •Experience with cloud data services or platforms such as Microsoft Azure, AWS, or Google Cloud, and with 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 (for example, 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, o