Data Manager

Data Manager 

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.