Data engineer

@ParasTech7

Hi, I’m a Principal-level Software Engineer with 21+ years of hands-on experience building scalable backend, cloud, data, and distributed systems. I personally lead architecture and critical implementation, with a small senior engineering team available when additional execution capacity is needed. For this project, my experience aligns well with AWS-based data engineering, including: • Scalable ETL/data pipelines and distributed processing • Apache Spark, Kafka, and event-driven architectures • AWS cloud architecture, S3, IAM, data processing, and automation • Python, SQL, Java, and high-performance backend systems • Data platforms, performance optimization, monitoring, and production troubleshooting • CI/CD, infrastructure automation, modernization, and reliability engineering I’m comfortable working with complex datasets and translating business requirements into reliable, scalable production systems. I focus on architecture, performance, maintainability, and clear communication. I’d be happy to discuss the existing architecture and how I can contribute to the project.

@dataspro

Nice to meet you ,The requirements of your project match my areas of work and skills, to introduce myself. My name is Anthony Muñoz and i am the lead engineer for DS Pro IT agency. I have worked for over 10 years as a Full-Stack and software development engineer and have successfully done multiple jobs. It will be a pleasure to work together to make your project. Feel free to discuss about the project with me, greetings.

@smitk9999

I understand you want an experienced data engineer to build and tune large, reliable AWS data pipelines that process huge volumes of financial data quickly, keep it accurate and compliant, and turn complex business needs into solid, cost-efficient solutions your analysts and regulators can depend on. I have experience on building large-scale ETL pipelines with Python, PySpark, AWS EMR, Glue, S3, Athena and Snowflake, using Parquet and Iceberg data lakes, Terraform and CI/CD, with strong data quality checks and query tuning to keep pipelines fast, stable and low cost. I can start work right away and contact me to discuss more details. Thanks. Smit

@farrukhdeveloper

Hi, This role interests me because it sits at the intersection of analytics, implementation, debugging, and stakeholder communication rather than being limited to dashboard creation. I’m a Software Architect with 18+ years of experience across web platforms, JavaScript, APIs, analytics, data pipelines, cloud systems, and enterprise integrations. I’m comfortable working with complex implementations where tracking accuracy, governance, and data quality matter as much as the reporting layer. My relevant strengths include: • JavaScript, browser/network debugging, cookies and local storage • Data-layer design and event mapping • Analytics implementation and validation • Tagging strategy and governance • API and server-side integrations • Data quality checks and reconciliation • Dashboard/reporting architecture • Privacy-aware tracking and consent integration • Technical documentation and stakeholder communication I can work closely with product, marketing, development, and privacy teams to translate measurement requirements into reliable technical implementations and troubleshoot issues down to the network-call level. I also bring architecture and team-lead experience, so I’m comfortable establishing standards, reviewing implementations, mentoring developers, and improving long-term maintainability. Regards, Farrukh Naveed Anjum Software Architect | Analytics, Data & Integration

@abdf2010

Hi, I am a professional web developer and I can do this project "Data engineer", I have 5 years of experience in web development. I have done many projects like this. I can do this job for you. I can start right now. Please contact me. Thanks

@Qloron0804

Hi, We can support your data engineering and analytics requirements with scalable data pipelines, cloud data platforms and analytics implementation support. For the Data Engineering scope, we can work on Python and SQL based ETL/ELT pipelines, large-scale data processing, AWS services, data lakes/warehouses, data quality, governance, observability, CI/CD and infrastructure automation. We can also support performance tuning, troubleshooting and cost optimization for production workloads. For the Adobe Analytics scope, we can support web analytics implementation, tag management, data layers, event mappings, tracking validation, debugging, reporting and documentation. We can also work with JavaScript, HTML, browser debugging, consent requirements and analytics QA workflows. Our data engineering and analytics capabilities cover data processing, cloud solutions, analytics and API based integrations. We can share relevant project details upon your response. A few questions: 1. Is this one combined requirement or two separate resources? 2. Which role needs to be filled first? 3. Is the engagement strictly onsite, or is offshore/remote delivery possible? 4. For Adobe Analytics, which implementation is currently used: AppMeasurement, Web SDK or both? 5. What is the expected engagement duration? Let’s get connected to discuss the required team structure and scope. Note: The final cost may vary based on the confirmed scope. Best Regards, Agnidipa Team Qloron

@michela542

Hi, I have experience developing data engineering pipelines, analytics platforms, data processing systems, and web analytics solutions using Python, SQL, AWS, and modern analytics tools. The most important part of this type of project is keeping large-scale data pipelines reliable while maintaining data quality, lineage, and accurate analytics tracking. In similar projects, I faced issues such as slow processing when handling large datasets, inconsistent data between source systems and analytics reports, and tracking events not firing correctly across different web flows. To solve these issues, I optimized SQL and distributed processing logic so large datasets could be processed more efficiently. For analytics problems, I used structured data layers and validated network requests and event mappings against the expected reporting data. As a result, the pipelines and analytics implementations became more reliable, data quality improved, and reporting was more consistent and easier to troubleshoot. I can help you with this kind of experience and contribute to both the data engineering and Adobe Analytics requirements. Looking forward to discussing your vision with you. Best regards, Michel

@TechWagger2026

Drawing on my 5+ years of dedicated experience as a Data Engineer, I am more than equipped to tackle the complexities of your project. Proficient in Python and advanced SQL, I have a deep understanding of ETL/ELT processes and the AWS ecosystem. My work has demanded intimate familiarity with platforms such as EMR, S3, Glue, Athena, IAM, Step Functions and Snowflake - skills that would be instrumental in optimizing your AWS data lake and ensuring compliance. Furthermore, my domain knowledge aligns astutely with your project requirements. Having worked extensively in the financial services sector in a similar capacity, I am familiar with regulatory environments and understand the nuances of payroll systems. As an additional asset let me add that we even specialize in AI solutions and integrating AI into engineering workflows so if you ever need to further augment your systems down the line we have it covered there as well. In sum, I offer not just solid technical abilities but also an alignment with your specific objectives that can greatly benefit your project's success. Consider TechWagger for diligent execution and comprehensive value addition throughout.

@Ryan15222

Hi, I’m an Engineer with 5+ years of experience developing connected systems, industrial data acquisition, automation and IoT solutions. I’m interested in supporting your data engineering projects, particularly where large-scale data processing connects with real-world systems and analytics. My relevant experience includes: - Python-based data processing and automation - Industrial IoT and sensor data pipelines - ESP32/STM32 systems generating high-volume telemetry - MQTT, REST APIs and system integration - SQL/database-oriented data handling - Data validation, monitoring and troubleshooting - Edge-to-cloud architectures - Siemens PLC / OPC UA data integration - Linux-based edge systems and Docker - Git-based development and deployment workflows I have worked on systems involving sensor telemetry, alarms, environmental data, industrial equipment and PLC data, including architectures where data is collected at the edge and transferred to higher-level applications for analysis. For an AWS/Spark-heavy production environment, I would first align with your existing architecture and coding standards, then work within the established S3/Glue/EMR/Athena/Snowflake ecosystem. I’m particularly interested in long-term offshore collaboration and can work effectively with distributed engineering teams and technical stakeholders. I’d be happy to discuss the current pipeline architecture, data volumes, processing requirements and expected role responsibilities. Best regards,

@ilyaashassiem

The main point I’d clarify before proposing the right resource is that the description appears to combine two highly specialised roles: senior AWS/PySpark data engineering and Adobe Analytics/AEP implementation. I can help coordinate the appropriate specialist profile around the required AWS, big-data and enterprise analytics capabilities rather than treating this as a generic full-stack role. I’d also want to verify the onsite and US work-authorisation requirements before confirming availability. Are you looking for one engineer who covers both JDs, or are these intended to be two separate positions? Regards, Ilyaas