Senior Data/BI Engineer Needed

@shraddhaa42

Hi, Hope you are doing well! Thanks for sharing your project requirement with me. It will be my great pleasure to work on your project. I have checked your requirement, and yes, I can do it because I have already worked on similar requirements in the past. I have the right skills to work on this assignment. I will complete the work as per your requirement.

@pranjaln64

Give me this opportunity and experience in pyspark etl pipeline and Microsoft azure. I am building a project like etl pipeline machine learning model deployment so, I am a hard worker

@debasishk54

Hello, Greetings!! I am an experienced BI engineer with a strong background in design, development, in ETL, data visualization in Azure ecosystem, MS Fabric, Azure Databricks, ADLS, ADF etc . I can work with you for your assignment. I have worked multiple projects using MS Fabric and databricks (precisely 2 each). My approach for this project: 1. Understand the business requirement and the timelines. 2. Data Integration: Populate source data in onelake, create snapshots in bronze layer 2. Transformation: create views in silver/gold layers to be used to populate the dim table and fact tables. Create notebooks to perform the transformations and rules implementation. Data quality checks. 4. User-Friendly visualization: Powerbi can be used for visualization to be connected to semantic model. 5. Other aspects: integration with github, access control and scalability will be taken care. I have successfully delivered similar projects and can ensure a high-quality, professional result within defined timelines. I look forward to discussing your requirements in more detail. Best regards, Debasish Karan

@Ravichandrap

senior associate with 7+ years of broad-based Experience in building data-intensive applications, overcoming complex architectural and scalability issues in diverse industries proficient in Predictive modelling, Data processing, Data mining, and scripting language Python. Capable of Creating, Developing, Testing, and Deploying highly adaptive services (AWS, IBM CPD) to translate business and functional qualifications into substantial deliverables.

@karthikrajak7

Hi, I’m a Senior Data Engineer with strong hands-on experience in PySpark, Microsoft Fabric, and Databricks, building scalable ETL/ELT pipelines for enterprise analytics platforms. I’ve worked extensively on real-world production challenges including schema drift, API inconsistencies, incremental load failures, pipeline recovery, and performance optimization across large datasets. My expertise includes Lakehouse architecture, Delta tables, Dataflows Gen2, Fabric pipelines, Unity Catalog, and modular PySpark development with production-grade monitoring and validation. I’m comfortable working independently within existing architectures, debugging complex pipeline issues, and delivering reliable, high-performance data solutions aligned with business needs.

@danishala

Hi, I can contribute as a hands-on Data Engineer and help strengthen your existing pipelines and BI workflows. In my recent work, I’ve built: * A real-time data pipeline using PySpark and Kafka (ingestion → transformation → aggregation with checkpointing and fault tolerance) * A batch processing pipeline handling structured data (XML-based ingestion, transformation, and optimization) This experience aligns closely with your requirements—especially around: * Building and maintaining PySpark pipelines * Handling schema inconsistencies and transformation logic * Debugging pipeline failures and improving reliability * Designing clean data flows (raw → processed → aggregated layers) I’m comfortable working independently within an existing architecture and focusing on practical problem-solving rather than just theoretical design. While my primary experience is with Spark-based pipelines, I’m also familiar with modern data platform concepts and can quickly adapt to tools like Microsoft Fabric or Databricks if required. If helpful, I can: * Review your current pipelines and identify bottlenecks * Improve performance and fault tolerance * Standardize ingestion and transformation logic * Ensure data quality and consistency across workflows Let’s connect and discuss your current setup—I can quickly get up to speed and start contributing. Thanks, Danish