Accellor
Reliability Engineer – Data & Cloud (Mid‑Level, Retail)
At Accellor, we are a trusted digital transformation partner that uses best‑of‑breed cloud technology to deliver superior customer engagement and business effectiveness for clients. We create an atmosphere that encourages curiosity, constant learning, and persistence. Employees are given the autonomy, collaboration, and delegation to grow their interests and take pride and ownership in their work.
Position Overview We are seeking a Mid‑Level Reliability Engineer to support and enhance the reliability, performance, and stability of our retail data and cloud platforms. This role will work closely with Data Engineering, Analytics, and Retail Operations teams to ensure store, inventory, and supply‑chain data are accurate, reliable, and available in real time.
Key Responsibilities
Support the reliability, performance, and uptime of data pipelines that power retail operations (POS data, supply‑chain feeds, inventory updates, etc.)
Monitor production workloads using Azure Monitor, Log Analytics, and custom dashboards
Respond to incidents, troubleshoot failures, perform root‑cause analysis, and implement prevention measures
Optimize ETL/ELT workflows using Azure Data Factory (ADF) for retail datasets
Automate system/Power BI integrations (e.g., POS, ERP, loyalty systems) using Azure Logic Apps
Implement quality checks, data validations, and alerting to ensure data freshness and accuracy
Write and optimize SQL queries and stored procedures supporting operational data stores
Work with Azure services including Storage Accounts, Key Vault, Azure Functions, Event Grid, and App Insights
Support CI/CD pipelines for data integration and Fabric workloads (Azure DevOps)
Develop and maintain Fabric Lakehouse pipelines to support reporting, forecasting, and analytics
Use Fabric Notebooks and PySpark for data transformations, batch processing, and scaling large retail data workloads
Collaborate with BI teams to ensure data is ready and reliable for dashboards and real‑time insights
Identify opportunities to automate manual processes and improve reliability across retail systems
Requirements
3-5 years of experience in Reliability Engineering, Data Engineering, Cloud Engineering, or similar roles
Strong hands‑on experience with:
SQL (debugging, tuning, modeling)
Azure Data Factory (ADF)
Azure Logic Apps
Microsoft Azure services (Storage, Functions, Key Vault, Monitor)
Solid understanding of monitoring, observability, and incident management
Strong analytical, problem‑solving, and communication skills
Ability to work in fast‑paced environments with frequent data updates (common in retail)
Preferred Qualifications
Experience in the retail industry (POS systems, inventory, supply‑chain, merchandising, or loyalty data)
Familiarity with Power BI or other visualization tools
Experience with Git, Azure DevOps, and CI/CD workflows
Practical experience with Microsoft Fabric, such as working with Lakehouse, Pipelines, or Dataflows through Notebooks and PySpark
Seniority Level Mid‑Senior Level
Employment Type Full‑time
Job Function Other
Industries IT Services and IT Consulting
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Position Overview We are seeking a Mid‑Level Reliability Engineer to support and enhance the reliability, performance, and stability of our retail data and cloud platforms. This role will work closely with Data Engineering, Analytics, and Retail Operations teams to ensure store, inventory, and supply‑chain data are accurate, reliable, and available in real time.
Key Responsibilities
Support the reliability, performance, and uptime of data pipelines that power retail operations (POS data, supply‑chain feeds, inventory updates, etc.)
Monitor production workloads using Azure Monitor, Log Analytics, and custom dashboards
Respond to incidents, troubleshoot failures, perform root‑cause analysis, and implement prevention measures
Optimize ETL/ELT workflows using Azure Data Factory (ADF) for retail datasets
Automate system/Power BI integrations (e.g., POS, ERP, loyalty systems) using Azure Logic Apps
Implement quality checks, data validations, and alerting to ensure data freshness and accuracy
Write and optimize SQL queries and stored procedures supporting operational data stores
Work with Azure services including Storage Accounts, Key Vault, Azure Functions, Event Grid, and App Insights
Support CI/CD pipelines for data integration and Fabric workloads (Azure DevOps)
Develop and maintain Fabric Lakehouse pipelines to support reporting, forecasting, and analytics
Use Fabric Notebooks and PySpark for data transformations, batch processing, and scaling large retail data workloads
Collaborate with BI teams to ensure data is ready and reliable for dashboards and real‑time insights
Identify opportunities to automate manual processes and improve reliability across retail systems
Requirements
3-5 years of experience in Reliability Engineering, Data Engineering, Cloud Engineering, or similar roles
Strong hands‑on experience with:
SQL (debugging, tuning, modeling)
Azure Data Factory (ADF)
Azure Logic Apps
Microsoft Azure services (Storage, Functions, Key Vault, Monitor)
Solid understanding of monitoring, observability, and incident management
Strong analytical, problem‑solving, and communication skills
Ability to work in fast‑paced environments with frequent data updates (common in retail)
Preferred Qualifications
Experience in the retail industry (POS systems, inventory, supply‑chain, merchandising, or loyalty data)
Familiarity with Power BI or other visualization tools
Experience with Git, Azure DevOps, and CI/CD workflows
Practical experience with Microsoft Fabric, such as working with Lakehouse, Pipelines, or Dataflows through Notebooks and PySpark
Seniority Level Mid‑Senior Level
Employment Type Full‑time
Job Function Other
Industries IT Services and IT Consulting
#J-18808-Ljbffr