AWS Native Data Platform Build - Native AWS Data Engineer

@tangramua

Dear ,   We carefully studied the description of your project and we can confirm that we understand your needs and are also interested in your project. Our team has the necessary resources to start your project as soon as possible and complete it in a very short time.   We are 25 years in this business and our technical specialists have strong experience in Amazon Web Services, AWS Lambda, Continuous Integration, Data Governance, PySpark, Apache Spark and other technologies relevant to your project.   Please, review our profile https://www.freelancer.com/u/tangramua where you can find detailed information about our company, our portfolio, and the client's recent reviews.   Please contact us via Freelancer Chat to discuss your project in details.    Best regards, Sales department Tangram Canada Inc.     

@AwaisChaudhry

Hello, I will design and implement a scalable, secure event-driven data platform on AWS using S3, SQS, Lambda, MWAA, EMR Serverless, PySpark, Apache Spark, Iceberg, Glue Catalog, Lake Formation, IAM, KMS, and Athena. This setup focuses on automated batch pipelines, governance, and secure, scalable data access. The architecture will create a data lake on S3 with Iceberg tables cataloged by Glue and orchestrated by MWAA. Events will trigger Lambda functions and SQS to start Spark jobs on EMR Serverless, with batch processing managed by Airflow DAGs. CI/CD will manage Spark notebooks and DAG deployments, while Lake Formation, IAM and KMS enforce governance and encryption. The result is a reusable platform with clear ownership, observability, and cost awareness that supports fast, compliant data access through Athena. What batch cadence and data volumes do you expect (daily/hourly) so I size S3, EMR Serverless and Spark resources accordingly? Which data sources must be ingested and in what formats, and what ingestion SLAs are required? What governance requirements are mandatory (Lake Formation policies, data classifications, IAM/KMS keys) and encryption standards? Do you require cross-region replication or a disaster recovery strategy, and what CI/CD approach do you prefer for DAGs and Spark jobs? What are your target SLAs for data freshness and query latency, and how will success be measured? Best regards,

@kumarashish99

As an AWS-certified professional with a strong background in backend development and DevOps engineering, I bring over 5 years of experience that perfectly aligns with your project requirements. Designing and building automated, scalable, and secure cloud infrastructures is my forte, and my expertise extends to integrating advanced AI/ML solutions for transformative insights - just the kind of platform you're seeking. Having worked extensively with AWS (including S3, SQS, Lambda, Glue Catalog etc.), I am well-versed in the native services you need for this project. Apart from the technical skills required (like PySpark and Lambda), I offer proficiency in enforcing data governance using frameworks like Lake Formation, IAM and KMS. Furthermore, my knowledge of deploying containerized applications on Kubernetes platforms complements your project's need for EMR Serverless. I understand that this endeavor is not ad-hoc ETL but rather requires building a robust platform. This resonates strongly with my approach – implementing Infrastructure as Code (Terraform, CloudFormation), designing CI/CD pipelines and automating deployment workflows are my areas of expertise that can ensure efficiency at scale. My focus on security - HIPAA, PCI-DSS, GDPR - makes me an ideal fit for your project which entails ensuring safe and secure data management. Let's connect and create an effective event-driven data platform together!

@Feriver

Hello, I understand you’re looking for a native AWS Data Engineer to help build and support an event-driven, platform-level data architecture using core AWS services rather than ad-hoc ETL scripts. I have hands-on experience designing AWS-native data platforms that emphasize automation, governance, and scalability, using services like S3, SQS, Lambda, MWAA (Airflow), and EMR Serverless to create reliable batch and event-driven pipelines. My focus is always on building systems that are repeatable, observable, and secure by default. I will help design and implement automated data ingestion and transformation workflows using PySpark and Apache Spark, with Apache Iceberg as the lakehouse table format and AWS Glue Catalog for metadata management. Data will be queryable via Athena with consistent schemas, versioning, and partition strategies. Governance will be enforced using Lake Formation, IAM, and KMS to ensure fine-grained access control, encryption, and auditability across datasets and environments. The outcome will be a clean, well-structured AWS data platform that supports batch processing, event-driven triggers, and long-term maintainability. I prioritize clear architecture, infrastructure-as-code alignment, and documentation so the platform can be extended confidently as data volume, teams, and use cases grow. Thanks Asif.

@robertw0802

Hi there!, I’m Robert, a Senior Full-Stack & AI Engineer with over 10 years of experience architecting and delivering SaaS platforms, automation systems, and intelligent applications, highlighting my top skills in AWS, data processing, and automation systems. I have successfully built event-driven data platforms using AWS services such as S3, Lambda, and EMR, focusing on automated batch pipelines. My recent project involved designing a scalable data lake architecture leveraging AWS Glue and Apache Iceberg for effective data governance and security. My deep technical background in both data engineering and AWS aligns seamlessly with your goals for a secure and efficient data platform. I can complete this project perfectly and deliver scalable, production-ready results. I am committed to clean architecture, structured documentation, and CI/CD automation practices. All data handling follows strict governance standards to ensure security and privacy. Let’s connect to refine your requirements and begin building a solution that exceeds expectations. What specific data governance standards will you require for this platform?

@sjohn117

Hi there, I am Sean, an AI & Full-Stack Developer with over 5 years of experience in building scalable SaaS platforms and data solutions, specializing in AWS services, data governance, and automated data pipelines. In a recent project, I successfully designed and implemented an event-driven data platform using AWS native services, achieving improved data accessibility and security for users. My expertise aligns perfectly with your project's requirements—by leveraging AWS services like Lambda, S3, and MWAA, I can build a robust data platform that is secure, scalable, and governance-compliant. I can do this project perfectly, ensuring your data is available efficiently. I typically deliver this scope in 10 days, including testing and necessary documentation. My approach includes implementing CI/CD best practices, ensuring clean code, and adhering to OWASP standards for security in all deployments. What specific challenges are you facing in your current data platform that you would like to address? Best regards,

@ivicab6

Hello, As a seasoned data engineer with over five years of solid experience under my belt, I couldn't be more excited about your project. You've outlined a challenging yet necessary task; one that requires building a secure, scalable and native AWS data platform. I assure you that my proficiency in Apache Spark, PySpark, and other relevant AWS services such as S3, Lambda, and Glue Catalog makes me an ideal fit for the job. In past projects, I have created automated batch data pipelines, designed effective data governance systems, and built secure platforms. Recent projects have exposed me to similar AWS platforms like Lake Formation and Amazon Athena. Additionally, I've integrated serverless technologies into my work, which aligns seamlessly with your needs. Moreover, my expertise extends to analytics and visualization tools like Power BI and Tableau – ensuring the valuable insights gained from your event-driven data platform can be efficiently accessed and presented. My dedication to transforming raw data into actionable solutions mirrors the level of commitment this project deserves. Looking forward to discussing how we can tackle this AWS Native Data Platform Build together! Thanks!

@devdeveloper813

Hello, As a Native AWS Data Engineer with Amazon Web Services as one of my core technical skills, I am well-equipped to tackle your project requirements. My experience spans 6+ years and includes building scalable data pipelines, managing data governance, and ensuring secure data accessibility - the core components of your project. Thanks!

@Ahmedh058

Hi there, I’m Ahmed from Eastvale, California — a Senior Full-Stack Engineer with over 15 years of experience building high-quality web and mobile applications. After reviewing your job posting, I’m confident that my background and skill set make me an excellent fit for your project — AWS Native Data Platform Build - Native AWS Data Engineer . I’ve successfully completed similar projects in the past, so you can expect reliable communication, clean and scalable code, and results delivered on time. I’m ready to get started right away and would love the opportunity to bring your vision to life. Looking forward to working with you. Best regards, Ahmed Hassan

@leciffre69

Timeline: 20 days | Cost: $15 / hour | Availability: 12h/day, ready to start today ❤️ Hello I’ve solved this exact problem before and can deliver a secure, event driven AWS data platform in 20 days. I have already reviewed your description fully and your main issue is building governed batch pipelines that scale without becoming fragile. In similar projects, I handled large-scale data ingestion where overlap was the biggest risk, such as scraping multi-location directories where the same domain appears repeatedly. To solve this, I use targeted ingestion, normalization, and strict deduplication so every dataset is unique, reliable, and analytics ready. This directly supports Iceberg, Glue, and Lake Formation consistency. To move forward, could you clarify: • Primary data sources and volumes • Governance rules already defined • Preferred orchestration patterns Looking forward to discussing more in detail on chat!

@adily1

Hi There, I understand that you're seeking a Data Engineer to build and support an event-driven data platform focusing on automated batch data pipelines and data governance. I am excited about the opportunity to leverage my expertise in AWS native services to deliver a robust and secure data solution. With over 6 years of experience in data engineering, I specialize in AWS services including S3, Lambda, and EMR Serverless, alongside data processing tools like PySpark and Apache Spark. My skills encompass building scalable data lakes and ensuring governance and security through best practices using Lake Formation and IAM. You can check my portfolio for examples of my previous work: https://www.freelancer.com/u/adily1 I look forward to collaborating on this exciting project and contributing to its success. Thank you, Regards, Adil Yousuf

@MSaadJaved

Hello saikrishna48, I will deliver a secure, scalable event-driven AWS data platform by: 1) assessing source and ingest requirements; 2) designing architecture using S3, Apache Iceberg, Glue Catalog, Lake Formation, IAM and KMS; 3) building automated batch/event pipelines with SQS, Lambda, MWAA (Airflow) and PySpark on EMR Serverless; 4) enabling querying via Athena and enforcing governance; 5) implementing monitoring, testing and CI/CD; and 6) documenting and handing over. I have hands-on experience with these services and platform-style implementations. Please come inbox to discuss requirements and next steps. Regards, Saad J.

@jonathanc360

Hello, I’m excited about the opportunity to help you build a robust, event-driven AWS data platform. Designing a secure, scalable, and automated data environment is exactly the kind of project I enjoy. My approach would start with understanding your current data flows and requirements, then designing batch pipelines using S3, Lambda, and EMR Serverless for PySpark processing. I’ll leverage AWS Glue Catalog and Apache Iceberg to organize your data lake, while enforcing governance and security using Lake Formation, IAM, and KMS. Queries will be optimized via Athena, and orchestration handled through MWAA (Airflow) to ensure smooth, repeatable workflows. I’ve built similar AWS-native data platforms where automated pipelines reduced manual intervention, improved data accuracy, and made actionable insights readily available for analytics teams. These platforms were fully secured, cost-efficient, and easy to scale as data volumes grew. The tangible benefits for you are reliable, automated data flows, full governance compliance, and a platform that grows with your business. I look forward to making this project a success and sincerely hope you’ll consider working with me.

@Coredev794

As a Data Engineer with extensive experience in AWS native services, I am excited about the opportunity to work on building and supporting your event-driven data platform. I specialize in automated batch data pipelines, data governance, and ensuring secure and scalable data availability. My expertise with AWS services such as S3, SQS, Lambda, MWAA, EMR Serverless, along with technologies like PySpark, Apache Spark, Apache Iceberg, AWS Glue Catalog, Lake Formation, IAM, KMS, and Amazon Athena make me well-equipped to contribute to the success of this project. I am committed to creating a robust and efficient platform that meets your specific requirements and objectives.

@josephm626

Good morning , How are you? I hope this proposal finds you well. I have checked your project (AWS Native Data Platform Build - Native AWS Data Engineer), which lies in the field of my certification & experience. This is to inform you that I have KEENLY gone through your project description, CLEARLY understood all the project requirements as instructed in your project proposal and this is to let you know that I will perfectly deliver as desired. Being in possession of all stated required skills like; Amazon Web Services, AWS Lambda, Apache Spark, Continuous Integration, PySpark and Data Governance:, as this is my field of professional specialization having completed all certifications and developed adequate experience in the respective field, I hereby humbly request you to consider my bid for professional, quality and affordable services that meet all your requirements. I always guarantee timely delivery and unlimited revisions where necessary hence you are assured of utmost satisfaction when working with me. Please send me a message so that we can discuss more and seal the project. WELCOME.

@DngPhgNam

✅Hi there, hope you are doing well! I have successfully built automated data platforms using AWS native services, similar to your project, where I implemented batch data pipelines and ensured data governance effectively. To successfully complete this project, a deep understanding of AWS services and experience in data governance are crucial, as they enable a seamless and secure data flow. I will leverage AWS resources such as S3, Lambda, and EMR Serverless to create a scalable and event-driven data platform, ensuring the data is secure and accessible. I'd like to work on this project sincerely from my confidence. Let's connect and discuss more.

@GenoraLabs

Hello saikrishna48, I see you are looking for a Data Engineer with expertise in AWS native services to build and support an event-driven data platform. I understand the importance of automated batch data pipelines, data governance, and ensuring secure and scalable data availability in a platform-style setup. My approach involves leveraging AWS services such as S3, SQS, Lambda, MWAA (Airflow), and EMR Serverless to create efficient data pipelines. I will also focus on implementing data governance using tools like Lake Formation and IAM, ensuring data security with KMS, and enabling querying capabilities through Amazon Athena. Core Deliverables: - Design and implement automated batch data pipelines - Set up data governance using Lake Formation and IAM - Ensure data security with KMS - Enable efficient querying with Amazon Athena Expertise & Portfolio: I'll share my portfolio with you in the DM. Kindly ping me there. My experience with AWS native services and data processing tools like PySpark and Apache Spark ensures quality, consistency, and a smooth delivery. I'd be happy to discuss your project further and answer any questions. Best regards, Malaika

@billybryan98

Hello, I am a data engineer specializing in AWS-native data platforms, focused on building event-driven pipelines, scalable data lakes, and strong governance. I work with a modern stack that includes S3, Lambda, SQS, MWAA, and EMR Serverless, combined with Spark-based processing to deliver reliable data products. In past projects, I set up production-quality platforms where batch processing is orchestrated by MWAA, data is cataloged with Iceberg in Glue, and governance is enforced with Lake Formation, IAM, and KMS. Analysts access data through Athena with secure, governed access, and pipelines scale as data grows. I can own this end-to-end, leveraging PySpark, Spark, and the AWS-native suite to deliver automated batch pipelines, governance, and secure data sharing. I will design a maintainable platform with clear milestones and CI/CD, ensuring reliability and security. Proposed timeline: 4–5 days with milestones for ingestion, processing, governance setup, and validation. Please feel free to contact me so we can discuss more details. I am looking forward to the chance of working together. Best regards, Billy Bryan

@TravisT007

I saw your project and am confident I can deliver on this. I'm currently working on a similar project and understand the importance of automated batch data pipelines, data governance, and secure data availability. By leveraging my expertise in AWS native services like S3, Lambda, and EMR Serverless, I can ensure a seamless event-driven data platform. Your project details emphasize the need for a platform-style setup, and I am committed to delivering a solution that not only meets but exceeds your expectations, providing you with a robust and scalable data environment. I invite you to view my portfolio, which showcases the quality and results of my past work. I look forward to hearing from you. Regards, Travis