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   i ntegrate   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 Q uality   A ssurance 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 e ffective 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 s kills 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.