Data automation Engineers Needed

@jinufeb14

As a highly experienced software engineer, I'm confident in my ability to design and implement the automation solutions you're seeking. I have a strong background in data transformation, utilizing languages such as Python and Scala (as per your preference) to create clean, uniform data models. Particularly, my expertise with respect to data cleansing will be invaluable in your integration process. Having worked on projects that demanded high levels of technical proficiency, I'm familiar with using Airflow and similar orchestration tools to create repeatable pipelines. These tools aid the efficient running of complex workflows and align well with the requirements of your project. Additionally, my use of Git for code management adheres to best practices and guarantees secure version control. Given my top 0.03% ranking on Freelancer.com, you can expect efficient and quality workmanship from me with a sharp eye for detail. Let's discuss timelines and move forward; because implementing this end-to-end automated process that drives accurate insights is something I am confident I can achieve!

@SamirBanna

Hello, I’m a Senior Software Engineer with extensive experience in Python automation and web scraping & C# WindowFormApp and WFP. I’ve carefully reviewed your requirements and I can deliver a reliable, production-ready solution — not a quick workaround. ✅ Clean and maintainable code ✅ Clear communication ✅ On-time delivery I’d be happy to discuss your project details and propose the best technical approach. Best regards, Samir

@Azursol

Hello Pushkar! I’m excited about the opportunity to help with your project. Based on your requirements, I believe my expertise in Python aligns perfectly with your needs. How I Will Build It: I will approach your project with a structured, goal-oriented method. Using my experience in Python, Software Architecture, Google App Engine, Hadoop, Scala, Data Cleansing, Data Integration, Data Governance, ETL, Data Modeling, I’ll deliver a solution that not only meets your expectations but is also scalable, efficient, and cleanly coded. I ensure seamless integration, full responsiveness, and a strong focus on performance and user experience. Why Choose Me: - 10 years of experience delivering high-quality web and software projects - Deep understanding of Python and related technologies - Strong communication and collaboration skills - A proven track record — check out my freelancer portfolio. - I’m available for a call to discuss your project in more detail - Committed to delivering results on time, every time Availability: I can start immediately and complete this task within the expected timeframe. Looking forward to working with you, Pushkar! Best regards, Ali Zahid India

@ahmed4499

Hello Sir I am computer engineer and i am certified Labview automation engineer so may i can help you , thanks ,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,

@Web1devloper

With my extensive expertise in data analytics and science spanning over eight years, I am confident about the value I can bring to your project. From the onset, my aim is to transform complex datasets into actionable business insights, and your consolidation project aligns well with my core competencies. My skillset includes Google App Engine and Python—skills that will be invaluable in designing reliable, repeatable pipelines and seamlessly integrating separate systems. Notably, I possess robust experience in data transformation which you've rightly emphasized as a key aspect of this project. through ensuring standardization, edge-case cleansing, field enrichment, and referential consistency. My knowledge of tools such as Python (Pandas, NumPy, Scikit-learn, Matplotlib, Seaborn), SQL (MySQL, PostgreSQL, Microsoft SQL Server), among others makes me well-equipped for efficiently achieving these goals for your project.

@Zoha37

With my well-honed skills in Python, I am confident in my ability to meet your project's integration needs. My strong suit lies in designing and implementing efficient, repeatable data pipelines, which aligns perfectly with your objective of consolidating and unifying various data sources into a clean, unified model. I understand the importance of data transformation for your project. I have ample experience in building logical and robust transformations that ensure standardized schemas, handle complex cleansing, enrich vital fields and maintain referential consistency. Furthermore, I believe my proficiency in Git will streamline collaboration while ensuring your project remains organized. Success for me is not just a fully functional pipeline but one that delivers zero data-quality exceptions as the barometer of efficiency. Letting you know what to expect from me, I'll provide modular transformation code and config-driven workflow definitions that will run seamlessly on Airflow, Prefect or any orchestrator you prefer. Lastly, I deeply value transparency; thus effective documentation demonstrating mapping rules and possible pipeline extensions will be provided. Given my skillset, experience and shared vision of success, undertaking this project would be an honour and I look forward to working with you towards achieving its greatness!

@Bwatter

Hello, I hope you're doing well. After carefully reviewing your requirements, I'm confident in my ability to meet them with the utmost accuracy in the shortest time possible as I have worked on similar projects. I have worked on similar projects as an expert where I delivered 100% quality. Chat me up as I'm available 24/7 via the freelancer.com app; let's discuss your project in detail and get started right away. Thank you.

@Hemanta013

This is a data pipeline consolidation effort where transformation quality and repeatable orchestration are the real priorities. I can own the end to end integration by refactoring the existing extract and load steps into a single automated workflow, with modular transformation logic that standardises schemas, handles edge cases, and enforces data consistency. The pipeline will be config driven, orchestrator ready for Airflow or Prefect, and easy to extend as sources evolve. If you can share the current scripts and target schema, I can confirm the approach and timeline quickly.

@yacinebsd

I understand your challenge: consolidating multiple datasets into a reliable, automated pipeline that standardizes, cleans, and enriches data while ensuring full referential integrity. I can help solve this problem and can start immediately. Using Python, I’ll create modular, configurable transformation scripts that integrate with your existing workflows, fully test the pipeline on sample data, and deliver clean, reproducible results. I’m a strong fit because I have extensive experience in end-to-end data engineering and ETL pipelines. I will guide you through a structured process: reviewing your raw datasets, designing transformation logic, implementing automated workflows, validating outputs, and documenting everything for easy future extensions. Please check my portfolio to see examples of my work. I’m happy to discuss the approach in more detail or provide a quick demo to ensure it meets your expectations. Looking forward for colaborating.

@HASEEB1803

This is exactly the kind of end-to-end data integration work I specialize in. I can join as one of the two data engineers and take full ownership of designing and implementing robust, repeatable transformation pipelines that unify data from multiple systems into a clean analytics-ready model. How I’ll approach it +Design a standardised target schema with strong referential integrity +Build modular, testable transformation logic in Python (Pandas / PySpark) +Handle edge cases: nulls, duplicates, schema drift, inconsistent keys +Enrich and normalise fields so downstream analytics are reliable +Refactor existing extract/load scripts into one cohesive automated workflow +Orchestration & automation +Config-driven pipelines runnable on Airflow or Prefect +Clear separation of extract, transform, and load stages +Easy extension for new sources or rules without code rewrites Deliverables you’ll get: +Clean, version-controlled transformation code in Git +Well-documented mapping rules and assumptions +A pipeline that runs on sample data with zero data-quality exceptions I focus on clarity, correctness, and maintainability, not just making the pipeline “run once.” If you want, we can quickly review your current scripts and I’ll outline a concrete execution plan and timeline. Happy to get started right away.

@syedabdullahh7

Hi, I’m AI/ML & Full-Stack Developer specializing in Agentic AI systems and intelligent automation. I have past experience in Data Engineering projects like this. My portfolio is available on my profile. PRICE NEGOTIABLE ➡️ Fast delivery | 100% satisfaction

@kend27

Hi, I’m an experienced data engineer with a strong track record building end-to-end data pipelines that consolidate disparate systems into unified, analytics-ready models. I specialize in Python/Scala transformations, schema standardization, edge-case cleansing, and ensuring referential integrity across complex datasets. I can take your existing extraction and loading scripts, refactor them, and design a modular, automated workflow using Airflow, Prefect, or your orchestrator of choice. Everything will be config-driven, version-controlled, and documented for clarity and maintainability. My goal is to deliver a pipeline that runs reliably on schedule or event triggers, producing fully populated target tables with zero data-quality exceptions. I’d be happy to discuss timelines and how we can get this operational quickly. Best regards, Ken

@shehrozsabir

Hi there, I read your requirements for consolidating data from separate systems. Since you already have basic scripts in place, I can help you refactor them into a clean, automated, and modular Python pipeline. My Approach to Your Project: Refactoring: I will take your existing raw scripts and break them into reusable, modular Python functions (standardizing schemas as requested). Data Cleansing: I will implement strict validation checks using Pandas to ensure zero data-quality exceptions. Automation: I can structure the code to be config-driven so it is ready to be triggered by your scheduler (Airflow/Prefect). I specialize in Python and Data Cleaning. I am available to start immediately and can dedicate my full time to getting this pipeline running smoothly. Best regards, Shehroz Sabir

@tranquilai

Hi there, this sounds like a classic consolidation challenge where the real value lives in the transformation layer, and that is exactly where this team focuses. The plan is to treat the pipeline as a single, cohesive product rather than a collection of scripts. Existing extract and load logic will be refactored into a clean, automated workflow, with the transformation layer doing the heavy lifting on schema standardisation, edge-case cleansing, enrichment, and referential integrity. Transformations will be modular, version-controlled, and config-driven so they are easy to extend as new sources come online. Orchestration will be handled through a scheduler like Airflow or Prefect, based on what best fits your current setup. Documentation will clearly spell out mapping rules, assumptions, and extension points so the pipeline remains maintainable long after delivery. Once sample data runs cleanly into a fully populated target table with zero exceptions, we know the job is done. Happy to walk through timelines and confirm the orchestration choice.

@CauaAlves

Hello! I'm a data engineer with strong Python expertise and hands-on experience building ETL pipelines for data consolidation projects. I've worked with Airflow, data transformation workflows, and schema standardization across multiple source systems. Understanding your needs: Design and implement end-to-end data pipelines that extract from multiple systems, transform into a unified model with clean schemas and referential consistency, and load into your analytics layer—all automated and repeatable. My approach: • Review your existing extraction/loading scripts and data sources • Design modular transformation logic in Python with clear mapping rules • Implement data cleansing, enrichment, and validation checks • Build config-driven workflows for Airflow/Prefect orchestration • Create comprehensive documentation covering schemas, assumptions, and extensibility • Test against sample data to ensure zero quality exceptions Deliverables: • Clean, modular Python code in Git • Workflow definitions ready for scheduling/event triggers • Complete documentation for maintenance and extension • Fully populated target tables passing all quality checks I can deliver this quickly and cleanly within your timeline. Ready to discuss next steps!

@Shivay7678

With my 4 years of experience in Data Analysis, I've honed a deep understanding of the importance of accurate and unified data models. My logistic and telecom projects background familiarized me with multiple systems, which developed my skills for integrating, standardizing, and ensuring referential consistency between various data sources. This skillset is crucial for your project as you intend to consolidate data living in several separate systems into a clean, unified model. My expertise extends to Python and SQL programming, data cleansing, and building data pipelines—I am more than comfortable with translating upstream extraction and downstream loading scripts to establish an integrated automated workflow. Having worked with similar orchestrators like Airflow and Prefect, I can confidently design config-driven workflows that are efficient and robust. Moreover, my experience in MIS reporting not only highlights absolute accuracy in my work but also emphasizes the importance I place on comprehensive documentation. I understand how crucial mapping rules, assumptions, and pipeline extensions are; therefore creating concise yet detailed records is second nature to me. By choosing me for your project, you're guaranteeing an end-to-end integration process that ensures zero data-quality exceptions.

@mbelenjunquera

Hello, I have extensive experience designing and implementing data-driven systems, with many years working on database architecture, data mapping, and system integration. My background includes end-to-end implementation and administration of complex IT systems, where data automation, consistency, and reliability were critical. I have led projects involving data flows between multiple systems, database optimization, and structured data transformation for operational and reporting needs. I work comfortably across the full lifecycle: understanding business requirements, designing data models, mapping and validating data, and ensuring automated processes are stable, traceable, and scalable. In addition to hands-on technical work, I bring strong project leadership skills, allowing me to communicate clearly with both technical and non-technical stakeholders and deliver solutions aligned with business goals. I would be glad to support your data automation initiatives with a practical, results-oriented approach. Best regards,