Why This Role Matters
We’re seeking a detail-oriented Data Manager to ensure the integrity and reliability of environmental quality data using the EarthSoft EQuIS suite. Your work will enable accurate analytics and reporting, driving informed decision-making for ERM’s technical teams and clients.
What Your Impact Is
You’ll oversee the entire environmental data lifecycle—from field and laboratory acquisition, through validation and QA/QC, to secure storage and reporting—ensuring accuracy, traceability, and compliance with regulatory and internal standards. By collaborating with cross-functional teams and interfacing with laboratories, you’ll deliver high-quality datasets that support technical consultants in producing analyses, maps, and models for environmental quality studies.
What You’ll Bring
- Hands-on experience with the EarthSoft EQuIS platform (especially Enterprise, Data Processor, DQM, Collect, EDGE), including data loading, validation, and reporting environmental studies.
- Strong environmental data literacy around the sample and data lifecycle: understanding of sampling plans, sampling points characteristics, sampling methods, soil description, analytes, detection limits, qualifiers, QA/QC routines, and regulatory requirements.
- Technical background in environmental sciences, data management, or related fields, with the ability to communicate technical and data management concepts clearly.
- Systemic, problem-solving and continuous improvement mindset, attention to detail, and a commitment to data quality and governance.
Key Responsibilities
- Manage data governance processes and ensure adherence to ERM’s compliance standards for environmental data.
- Oversee the data lifecycle and integrate data from laboratory, field, and historical sources as EDDs into ERM’s EQuIS™ databases and other data systems considering acquisition (field and lab), validation (EDP), QA/QC (internal protocols and DQM), archiving, and querying and reporting through EQuIS Enterprise, PowerBI API and Excel outputs in different formats.
- Collaborate with internal teams and laboratories to plan and prepare for sampling rounds and ensure timely and accurate data delivery, including troubleshooting EDD/EDP errors and supporting field data collection (Collect/EDGE).
- Apply Quality Assurance protocols, including completeness checks, duplicates, logical errors, unit/qualifier alignment, metadata management, issuing quality queries and reports for technical consultant assessments and managing reportable data in EQuIS for consumption in official querying and reporting.
- Support enterprise analytics and reporting by providing clean, structured datasets and generating standard EQuIS reports and Power BI/Excel summaries or preparing EQUIS outputs for 3D modelling in EVS or in GIS formats.
Required Qualifications
- Bachelor’s or Master’s degree in Environmental Sciences, Data Management, Information Systems, Computer Science, or a related field (environmental background strongly preferred).
- At least 3 years of experience in environmental data management and data quality roles, including hands-on experience with EarthSoft EQuIS modules: EDP, Data Manager/Enterprise, Collect, and EDGE.
- Strong knowledge in EQuIS schema, data tables and structure, as well as on data management best practices.
- Experience with QA/QC routines for environmental data (validation, qualifiers, non-detects, duplicates, holding times).
- Active and effective English communication skills, with the ability to translate technical findings into actionable insights for project teams.
- Ability to manage workload independently and adapt to changing deadlines.
- Comfortable working in a computer-based, desk-oriented environment.
Preferred Qualifications
- Experience with EQuIS Modules: SPM, DQM Format customization, DQM rule authoring, and Collect/EDGE form design.
- Familiarity with Python scripting for ETL, QA automation, or data normalization.
- Experience with programming languages such as R, Python, or similar.
- Experience with GIS tools (ArcGIS/QGIS) for geospatial data visualization and mapping.
- Intermediate skills in Power BI or Excel for environmental data visualization and reporting.
- Knowledge in laboratory analytical methods and tests.
- Knowledge of laboratory data systems, LIMS workflows, and electronic data deliverables (EDD/SEDD).
- Exposure to cloud-based data platforms, SharePoint, or Power Automate for workflow integration.
