Beyondsoft Consulting
Data Engineer
Remote Data Engineering role with clear candidate location fit.
PostedJun 20, 2026
Eligible countries64 accepted countries
Seniority signalMiddle, Senior
Work settingRemote
Accepted candidate locations
Role overview
Data Engineer
Requirements and responsibilities
Readable role content extracted into sections for faster review.
WHAT YOU WILL BE DOING:
- Design, build, maintain, monitor, and troubleshoot data-processing automations, including data preparation, publishing, transformations, error handling, retry mechanisms, and conditional workflows.
- Develop and maintain data ingestion pipelines from external sources into SQL databases. Manage datasets, linked services, copy activities, and pipeline scheduling.
- Create and support automated flows to trigger Logic Apps and handle lightweight processes such as report refreshes, dataflow updates, notifications, and approval workflows.
- Develop, enhance, and maintain canvas apps and standalone internal applications to support business needs.
- Perform full-stack BI development, including data modeling, DAX development, Power Query (M), semantic models, row-level security (RLS), workspace management, and report publishing. Leverage Microsoft Fabric as the unified access platform for portal activities.
- Manage and administer Azure resources including Logic Apps, Data Factory, storage accounts, monitoring solutions, RBAC, Application Insights, and Log Analytics. Ensure alignment with S360 security and compliance requirements.
- Design and maintain standardized Excel templates, support Excel-to-database ingestion workflows, and validate raw source data.
- Troubleshoot and resolve issues across complex ETL processes and data pipelines.
- Monitor and manage alerting for failures in Logic Apps, ADF pipelines, Power Automate flows, and Power BI refreshes.
- Govern Power Platform environments, including environment management, licensing, and compliance.
- Implement and maintain security controls (Azure RBAC, Microsoft Entra ID, S360 alignment, Power BI RLS).
- Manage change control, versioning, and documentation for automations, SQL artifacts, and reporting assets.
- Optimize performance and scalability across data pipelines and reporting solutions as volumes grow.
- Conduct root-cause analysis to reconcile discrepancies between Excel, database systems, and reporting outputs.
- Collaborate with vendors and development teams to quickly identify and resolve technical issues.
- Read, modify, and extend existing hard-coded queries and publishing logic as needed.
- Perform basic scripting for bulk operations, diagnostics, or automation support.
- Perform additional duties as assigned.
MINIMUM QUALIFICATIONS:
- 5+ years of experience in data engineering, BI development, automation engineering, or related technical roles.
- Strong hands-on experience with Azure Data Factory (ADF), including pipeline development, datasets, linked services, scheduling, monitoring, and troubleshooting.
- Experience developing and maintaining Logic Apps and Power Automate workflows for operational automation and integrations.
- Advanced SQL development skills including query optimization, stored procedures, ETL development, and troubleshooting complex data transformations.
- Strong experience with Power BI development including: Data modelingDAXPower Query (M)Semantic modelsRow-Level Security (RLS)Workspace administration and publishing
- Data modeling
- DAX
- Power Query (M)
- Semantic models
- Row-Level Security (RLS)
- Workspace administration and publishing
- Experience with Microsoft Fabric and enterprise BI/reporting platforms.
- Experience administering Azure resources including RBAC, Application Insights, Log Analytics, Storage Accounts, and monitoring solutions.
- Experience supporting Excel-to-database ingestion processes and validating source data integrity.
- Ability to troubleshoot and resolve issues across ETL pipelines, reporting systems, and automation workflows.
- Experience implementing security and governance controls across Azure and Power Platform environments.
- Strong analytical and problem-solving skills, particularly in reconciling data across multiple systems.
- Ability to maintain thorough documentation, including runbooks and process workflows.
- Attention to detail and a proactive approach to monitoring, troubleshooting, and continuous improvement.
- Occasional infrequent in person activity may be required.
Details
- Data modeling
- DAX
- Power Query (M)
- Semantic models
- Row-Level Security (RLS)
- Workspace administration and publishing
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