We’re looking for a skilled developer to build an automated data pipeline that pulls weekly Profit & Loss (P&L) statement attachments from a designated email inbox and processes them into our Azure data environment. Key Responsibilities: • Monitor a specific email inbox and extract attached P&L files (Excel or CSV format) • Land the files in Azure Blob Storage or directly into a staging database • Normalize and transform the data into a clean, consistent structure (e.g., pivot/unpivot rows, align columns) • Ensure the dataset is report-ready for downstream consumption • Load transformed data into our Azure SQL Data Warehouse • Push the cleaned data into an existing Azure Analysis Services tabular model for use in Power BI Requirements: • Strong experience with Azure tools (Blob Storage, Data Factory, Logic Apps, or Functions) • Data wrangling and transformation expertise (Python, T-SQL, or ADF mapping data flows) • Familiarity with data modeling and tabular model structures • Ability to build fully automated and repeatable workflows The solution should run on a weekly schedule and require zero manual intervention once deployed.
Keyword: Data Cleaning
Price: $85.0
SQL Microsoft SQL Server Microsoft SQL Server Programming Python
Scope – Make the overall Excel book cleaner and more uniform without changing the overall layout. Separate out the contract labor data on the Mon – Sunday tabs on the Phase code tab per company.
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