Automate Azure Databricks Data Ingestion

@seefattechnologi

Hi!^^^^^^ I have hands-on experience with Azure Databricks, Power Automate, SQL, and automated data pipelines. I can build a reliable end-to-end solution that fetches data via ODBC, loads it into Delta tables, automates cleanup and scheduling, and provides clear documentation for easy future maintenance. Thanks!! Parminder

@himanshus642

With my background in Full Stack development and a solid 5+ years of experience under my belt, I firmly believe I'm the best fit for automating your Azure Databricks data ingestion project. My expertise in building scalable automation-driven applications and working with technologies like SQL, Power Automate, and Databricks aligns perfectly with what you're seeking to accomplish. One key attribute I bring to the table is my past involvement in similar projects emphasizing automation. For instance, I recently helped develop an automated financial system with robust security measures ensuring operations like yours were completed without any manual intervention. I incorporate a milestone-first approach, which not only streamlines the process but guarantees distinct documentation—perfectly fitting acceptance criterion 4. Crucially, I prioritize clear communication throughout projects, keeping clients well-informed about every stage of development. You'll never be kept guessing about progress and my adaptability and professionalism ensure that any tweaking you need done —be it schedule frequency, query parameters or target tables — will be taken care of efficiently. So why wait? Let's make your fully automated pipeline a reality!

@mobasherreza10

As an experienced developer with a solid foundation in automation, Azure, and data management, I can deliver you the seamless pipeline that you need to automate your data-lake. With proficiency in SQL and Power Automate, I can architect connectors, triggers, and error-handling mechanisms from scratch making sure your third-party analytical data is cleanly deposited into Azure Databricks. Additionally, my proficiency with ETL will be pivotal when configuring the flow to ensure incoming records land into correct Delta tables. On top of that, my capabilities extend to DevOps and I can create a Databricks job callable from the same flow, which removes stale records keeping your tables up-to-the-minute so that they only contain the latest daily snapshot. You can expect an end-to-end solution that sprints through each day's run in under 15 minutes - all without any manual intervention.

@techsty2014

Hey, We will build your full ingestion pipeline: ODBC query, Power Automate cloud flow, Delta table writes, and a Databricks cleanup job, all scheduled to run daily with success/failure alerts. For the stale-data purge, we will use Delta MERGE keyed on your primary keys. This avoids accidental deletes during partial loads and keeps the table transaction log clean for time-travel queries if you ever need to audit a previous snapshot. A couple of quick things to confirm: 1) Which external system are we connecting to via ODBC (specific driver and auth method)? 2) How many tables and roughly how many rows per daily pull are we expecting? The number quoted here is a starting estimate. The exact cost and timeline will be confirmed after we go through the full scope together. Looking forward to your response. Best regards, Faizan

@mayr81

Your pipeline goal is clear: an unattended, end-to-end Azure Databricks ingestion that starts from a third-party analytical source and lands clean daily Delta snapshots with no manual steps. I can design the full solution to meet your “single button deploy” acceptance criteria by provisioning the Azure resources, wiring Power Automate triggers/connectors, and generating the Databricks job + notebook that performs safe stale-record purges while preserving primary keys. Implementation approach: - Create an ODBC-based SQL extraction query optimized for incremental daily loads. - Build a new Power Automate cloud flow from scratch: connector setup, parameterized query execution, robust error handling/retry, and writing to the correct Delta tables. - Author a Databricks notebook/job invoked by the flow to enforce “latest daily snapshot only” semantics, deleting records older than the current load window without breaking keys. - Add a 24-hour scheduler and success/failure notifications. Delivery includes concise documentation covering: updating schedule frequency, adjusting query parameters, and changing target Delta tables safely.

@Olywebart

Hello there, Building an automated data pipeline that eliminates manual steps while delivering fresh data daily is crucial and totally doable with your Azure Databricks setup. Your goal for a seamless, scheduled ingestion with zero manual touchpoints is exactly the kind of challenge I thrive on. I've integrated complex SQL queries directly into automated workflows before, ensuring data lands clean and current in Delta tables. For your project, I propose: 1) architecting the Power Automate flow with robust connectors and error handling, 2) crafting the ODBC SQL query to fetch only necessary analytic data, and 3) setting up the Databricks job to reliably purge stale records daily. We'll ensure the entire solution deploys with one click, runs within your 15-minute window, and includes clear, adjustable documentation. I can deliver an initial version within a week and am happy to sync briefly anytime to align expectations. Could you share more about the types of analytical data and primary keys involved for tailoring the SQL query? Thanks, Anatolie

@Specgi

I am an experienced data engineer with expertise in Azure Databricks, data pipelines, and cloud-based ETL/ELT automation. I can design and implement a scalable, reliable data ingestion solution that automates the movement of data from your source systems into Azure Databricks while ensuring high performance, security, and data quality. My approach includes building automated ingestion workflows using Azure Databricks, integrating with services such as Azure Data Factory, Azure Storage, or other required data sources, and implementing monitoring, logging, and error-handling mechanisms. I will optimize the pipeline for incremental loads, scheduling, and scalability, ensuring your data is processed efficiently and is ready for downstream analytics. I am committed to delivering a well-documented, maintainable solution that aligns with your business and technical requirements. Throughout the project, I will provide clear communication, regular progress updates, and thorough testing to ensure a smooth deployment and reliable long-term operation. I look forward to helping you streamline your Azure Databricks data ingestion process.

@OscarMozo

Hi, I can help you with this. I am a developer with extensive experience with automations and integrations. I've helped clients with similar projects. Let me know your interest, Sincerely, Nicolas