Position Overview
Inventive Technologies Corporation is seeking an ETL / Data Analytics Developer to design, build, and support end-to-end data solutions—from data ingestion and transformation through analytics, reporting, dashboards, and user-facing data products.
This role combines hands-on data engineering, ETL development, analytics, and data visualization. The developer will integrate data from multiple applications and external sources, build reliable and reusable data pipelines, create analytics-ready datasets, and develop intuitive ways for users to explore and understand the resulting information.
The ideal candidate is comfortable working across the entire data lifecycle: understanding source systems and business requirements, developing backend data-processing logic, validating data quality, and presenting data through dashboards, reports, visualizations, or lightweight analytical applications.
Key Responsibilities
- Design, develop, maintain, and enhance ETL and data-integration pipelines.
- Extract and ingest data from databases, application systems, files, APIs, and external sources.
- Develop transformation logic to cleanse, standardize, validate, join, reconcile, aggregate, and enrich data.
- Build and maintain data structures supporting operational reporting, analytics, dashboards, and downstream applications.
- Develop SQL and PL/SQL for data extraction, transformation, validation, and analysis.
- Create automated data-quality controls to identify missing, invalid, inconsistent, duplicate, or anomalous data.
- Investigate pipeline failures and data discrepancies, perform root-cause analysis, and implement corrective solutions.
- Monitor scheduled processing jobs and improve their reliability, maintainability, and performance.
- Develop source-to-target mappings, transformation specifications, data definitions, and technical documentation.
- Work with business analysts, data owners, application developers, and end users to understand data structures, definitions, reporting needs, and analytical requirements.
- Build curated, analytics-ready datasets that can be reused across reports, dashboards, and analytical applications.
- Perform exploratory data analysis, profiling, reconciliation, and trend analysis.
- Develop queries, views, APIs, data services, or extracts that expose curated data to reporting and visualization layers.
- Design and develop interactive dashboards, reports, visualizations, and data-driven user interfaces.
- Translate business questions and KPIs into intuitive visual presentations that allow users to move from high-level trends to supporting detail.
- Develop drill-down, filtering, search, slicing, and other interactive capabilities that improve data usability.
- Build or support lightweight analytical applications where dashboards alone are insufficient.
- Ensure visualizations and analytical products accurately reflect approved business rules and authoritative data sources.
- Automate refresh and publication processes so reports and dashboards remain current without unnecessary manual intervention.
- Collaborate with application developers when data functionality spans both backend processing and user-facing application components.
- Participate in Agile sprint planning, backlog refinement, technical reviews, testing, release readiness, and production deployment.
- Develop automated tests and reconciliation procedures for data-processing and analytical workflows.
Data Presentation and Analytics Responsibilities
The position is expected to work beyond backend data processing and contribute directly to how data is consumed by users. Responsibilities may include:
- Creating dashboards and visualizations using tools such as Databricks, Power BI, Tableau, R Shiny, or comparable platforms, as well as custom applications.
- Developing browser-based or application-integrated data views using JavaScript, HTML/CSS, or approved visualization frameworks.
- Building analytical applications that combine filters, visualizations, tabular detail, and business logic.
- Designing role-appropriate views for executives, managers, analysts, and operational users.
- Working with stakeholders to identify meaningful metrics, KPIs, dimensions, and drill-down paths.
- Applying user-centered design principles to make complex information understandable and easy to navigate.
- Supporting accessible data presentation and Section 508/WCAG-compliant visualizations where required.
- Evaluating when a dashboard, report, embedded visualization, or custom analytical interface is the most appropriate way to present information.
Required Qualifications
- Bachelor’s degree in Computer Science, Information Systems, Data Engineering, Data Analytics, or a related technical discipline, or equivalent relevant experience.
- 5+ years of experience developing ETL, data-integration, data-warehouse, analytics, or database solutions.
- Strong SQL development skills and experience working with complex relational data.
- Experience designing and maintaining ETL/data pipelines, including extraction, transformation, loading, validation, error handling, and reconciliation.
- Experience with Oracle and/or other enterprise relational databases.
- Strong understanding of relational data modeling, joins, keys, dependencies, normalization, and analytical data structures.
- Experience troubleshooting data-quality and data-integration problems across multiple sources.
- Experience creating datasets or data services for reporting and analytics.
- Experience building reports, dashboards, visualizations, or other user-facing data products.
- Ability to translate business requirements into both backend data logic and front-end analytical solutions.
- Experience working in an Agile software-development environment.
- Strong documentation, analytical, and communication skills.
Preferred Qualifications
- Experience with PL/SQL and Oracle.
- Experience with Talend, Informatica, SSIS, or comparable ETL/data-integration tools.
- Experience with Python and/or R for data processing, analytics, automation, or visualization.
- Experience with Power BI, Tableau, R Shiny, or similar BI/analytics platforms.
- Experience developing visualizations or data-driven interfaces using JavaScript or modern web technologies.
- Experience building APIs or services that expose data to applications or visualization layers.
- Familiarity with dimensional modeling, reporting schemas, data marts, and semantic models.
- Experience with metadata management, lineage, governance, or data-quality frameworks.
- Familiarity with REST APIs, JSON/XML, flat-file processing, and secure file-transfer mechanisms.
- Experience with advanced analytics techniques such as classification, clustering, anomaly detection, entity matching, or text analytics.
- Experience supporting enterprise or government data environments.
- Familiarity with accessibility requirements for dashboards and web-based analytical products.
What Success Looks Like
A successful ETL / Data Analytics Developer does more than move data between systems. You will help create the complete path from raw source data to usable information.
You will understand how data is generated, how it should be transformed and validated, how it should be structured for analysis, and how users should ultimately interact with it. You will be able to diagnose why numbers do not reconcile, improve the underlying pipeline, and then help present trusted information through dashboards, reports, visualizations, or analytical applications that users can understand and act on.
The role requires someone who is comfortable working across both backend data engineering and front-end data presentation, connecting reliable data pipelines with practical, user-friendly analytical products.