Experienced Data Engineer Needed

@Prutheus

Let me answer your requirement list honestly rather than claim the full set, because you will find out in week one anyway. Strong and in production for me: Python, SQL, Apache Airflow, and cloud on AWS and Azure. I run Airflow pipelines 24/7 for industrial clients — orchestration, retries, backfills, alerting on silent failures, the operational side that separates a pipeline that works from one that is trusted. PostgreSQL and data modelling are my core, including a platform consolidating 14 upstream sources into one warehouse layer. Where I am honest about the gap: Apache Spark and dbt I know conceptually and have read into, but I have not run them at production scale. Snowflake, BigQuery and Databricks likewise — I have worked the equivalent problems on Postgres and Azure, not on those specific engines. If your pipeline is Python, SQL, Airflow and cloud, I am a strong fit and can start immediately. If the day-to-day is heavy Spark and dbt on Databricks, someone else is the better hire and I would rather say so now. I work German engineering standards: tested code, documented decisions, no silent data loss. An open monthly contract suits me. Question: what does the actual stack look like day to day, as opposed to the wish list? Martin

@kumarashish99

As an AWS-certified professional with over five years of experience in backend development, DevOps engineering, and Kubernetes orchestration, I believe I'm the perfect fit for your remote Data Engineer position. I've built scalable, secure, and efficient cloud infrastructures with a strong focus on integrating AI/ML solutions to maximize business outcomes - skills that line up flawlessly with your needs. My technical expertise is primarily in Python and SQL, which I employ for efficient data management and manipulation. Furthermore, I have hands-on experience working with Apache Spark and modern data pipelines such as dbt. My knowledge of Snowflake, BigQuery, Redshift, and Databricks will allow me to adapt seamlessly to your existing infrastructure. I am passionate about what I do and pride myself on my ability to handle high-pressure situations while delivering quality work within deadlines. I'm excited about the possibility of becoming part of your remote team on this important project and look forward to discussing how my skills could contribute to its success further!

@Web1devloper

With a robust background in Data Analytics & Science spanning 8+ years, I am convinced that I possess the ideal skill set for your project. Specializing in data storytelling, dashboarding, and end-to-end data solutions, I have honed strong Python and SQL skills, along with hands-on experience in Apache Spark, just as you require. Furthermore, my expertise in Airflow, Dagster, dbt, and modern data pipelines could power the efficient handling of your remote technical project. On top of the essential qualifications you mentioned, I have additional experience with AWS and Google Cloud Platform (GCP) that would be beneficial for a streamlined collaboration given you intend to select globally. My extensive knowledge in data modeling and Git workflows would come handy in ensuring secure and organized project management—a crucial aspect of any project. My familiarity with a wide range of analytics tools like Excel, SQL, BigQuery among others would ensure a hassle-free flow of work. Moreover, I am well-acquainted with diverse domains such as finance, healthcare, e-commerce & SaaS—this allows me to contextualize insights based on real-world applications; offering sound solutions to optimize operations and forecast outcomes. Choose me for the job and we will unlock the full potential of your data!

@mahads31

As a seasoned data engineer with over four years' experience and proficiency in Python, SQL, and various modern data engineering tools, I am confident in my ability to handle the demands of your project. I have been working extensively with Apache Spark, Airflow, Dagster, dbt, and Snowflake - all of which were listed as key requirements for this job. My past projects include building production data pipelines and I'm well familiar with AWS and GCP to manage any infrastructure needs along the way. Additionally, my familiarity with CI/CD practices and containerization through Docker has enabled me to maintain highly efficient and scalable systems. Being experienced with CI/CD practice through Terraform, furthermore means that maintaining an efficient pipeline for your data operations will not be a challenge. Finally, my love for technology, focus on efficiency, and my commitment to creating lasting client relationships make me an ideal fit for your project. Pitch: Having delved into the IT industry full swing from web development to automation to AI Automation. Today I stand here combining all those skills around the world of data engineering. Delivering solutions tailored to the unique requirements of different industries has honed my problem-solving prowess while managing international clients reaffirms my excellent communication skills in English - a strength within remote teams.

@alluankit01

Hi, I can support your remote Data Engineering project with strong Python, SQL, Spark, modern orchestration, dbt pipelines, cloud data platforms, and production workflow experience. The best solution is to first understand your current data sources, warehouse/lakehouse platform, pipeline schedules, transformation logic, data-quality expectations, and Git/deployment workflow. Then I’ll help build, maintain, and optimize reliable data pipelines using Python, SQL, Spark, Airflow/Dagster/Prefect, dbt, and cloud platforms like Snowflake, BigQuery, Redshift, or Databricks. I’m comfortable with Python, SQL, Apache Spark, Airflow, dbt, data modeling, warehouse design, AWS/Azure/GCP, Databricks, BigQuery/Snowflake-style platforms, Git workflows, production pipeline debugging, data quality checks, and documentation. Support can include: * Data pipeline development * SQL and Python transformations * Spark jobs * dbt models * Airflow/Dagster/Prefect workflows * Cloud warehouse support * Data modeling * Pipeline monitoring/debugging * Git-based collaboration * Documentation and handover notes I’m comfortable working remotely with international teams, communicating clearly in English, and overlapping with US business hours as needed. I’ll focus on clean, reliable, and maintainable data pipelines that support production use. Best regards Ankit

@vinod150987

Hi, I’m an experienced Data Engineer with strong hands-on expertise in Python, SQL, Apache Spark, Airflow, dbt, cloud platforms, and production-grade data pipelines. I’d be excited to contribute to your remote technical team. I can help with: * Building and maintaining reliable ETL/ELT data pipelines * Developing scalable data processing workflows using Python, SQL, and Spark * Creating and orchestrating workflows with Airflow * Implementing modern transformation pipelines with dbt * Working with cloud data platforms such as Snowflake and Databricks * Data modeling, warehouse design, and performance optimization * Developing production-ready pipelines with proper Git, testing, monitoring, and CI/CD workflows * Working with AWS/Azure environments * Improving data quality, reliability, and pipeline observability I’d be happy to discuss your current data stack, project requirements, and how I can contribute from day one.

@designerbros

I'm Boobesh Kumar, co-founder of Designer Bros and Custom Software Engineer. We specialize in engineering high-throughput production data pipelines, modern data stack architectures (dbt, Airflow, Snowflake/Databricks), and cloud data infrastructure across AWS, GCP, and Azure. We can take complete technical ownership of your data engineering pipeline—building, optimizing, and maintaining scalable batch and real-time ETL/ELT workflows that ensure zero-downtime data delivery and strict data quality. Technical Capabilities & Stack Alignment Core Processing & Pipelines: Strong expertise in Python, complex SQL, and distributed processing using Apache Spark (PySpark) alongside dbt for modern data modeling (Star Schema, Data Vault 2.0). Orchestration & Workflow Management: Production experience building, monitoring, and debugging DAGs in Apache Airflow, Dagster, and Prefect. Data Warehousing & Lakehouses: Query optimization, partitioning, and schema management across Snowflake, Databricks, BigQuery, and AWS Redshift. Cloud & DevOps Infrastructure: Hands-on experience with AWS (S3, EMR, Glue, Lambda), Azure, and GCP, paired with Docker, Terraform, and Git/GitHub Actions for automated CI/CD deployment pipelines. Streaming & Data Quality (Nice-to-Have): Event streaming via Apache Kafka / AWS Kinesis and automated data validation test suites (Great Expectations / dbt tests).

@NEHABHAT92

I understand that my background primarily lies in web and mobile app development, which may not immediately align with your current need for a Data Engineer. However, with 9+ years of experience as an IT professional, **I bring a unique perspective to the table**. My proficiency in Python, a language crucial to data engineering, would make transitioning into this role seamless for me. Moreover, while I may lack specific experience with data related technologies like Apache Spark or Airflow, I have honed my skills as a fast learner throughout my career. In combination with my proven ability to efficiently collaborate in remote teams and having worked with production data pipelines regularly in the past, I believe I can competently contribute to your project. Lastly, I understand that this is not just a programming job but also requires strong communication skills. As evident through this pitch, I bring excellent written and spoken English skills as well as the determination to provide quality work to my clients. Summarily,I offer adaptability, meticulousness and dedication as your Data Engineer. I am eager to learn and grow alongside your team on this project.

@jagratip3

Hi, I’m interested in joining your remote Data Engineering project and can contribute across Python/SQL development, production data pipelines, ETL/ELT workflows, and cloud-based data platforms. I’m comfortable working with Python, SQL, Apache Spark, Airflow/Dagster/Prefect, dbt, Git, and modern data warehouse architectures, with a strong focus on building reliable, maintainable pipelines rather than one-off scripts. I can also work with platforms such as Snowflake, BigQuery, Databricks, and AWS/Azure/GCP depending on the project environment. My approach emphasizes clean data modeling, automated testing, monitoring, error handling, documentation, and reproducible deployments. I’m also comfortable collaborating with international teams and maintaining overlap with US business hours. I’d be happy to discuss the existing architecture, project requirements, expected responsibilities, and monthly contract scope through Freelancer. Best regards, Jagrati

@Abxnfotech

As an organization, we are dedicated to pioneering innovative technology solutions while maintaining the highest standards of quality. I, Shakti an running with a wide range of software including Python have spent my past years developing skills that resonate deeply with your project description. I'm experienced in Data Engineering, well versed with Python and SQL, have hands-on experience with Apache Spark and proficient in dealing with databases such as Snowflake, BigQuery, Redshift, and Databricks. Moreover, I've successfully executed environment setups on various cloud platforms like AWS and GCP. And the work didn't stop there. I believe in continuous integration and deployment, and therefore am familiar with tools like Terraform along with strong experience in CI/CD practices. Additionally I understand the significance of version control in data engineering projects and utilize Git workflows actively But most importantly, I not only match up to your requirements but also bring a few extra qualities to the table - advanced knowledge in Kafka, Kinesis and Flink, containerization using Docker and orchestration using Kubernetes for scalable and efficient applications. To ensure data quality and observability ،I've worked extensively خدمة-العملاء Data Observability Platforms 。Expectations from cloud environments are soaring high therefore I am completely onboard Experience working on kubexyz

@MuhammadAsad108

✔ I deliver 100% work — 99.9% is not for me. ✔ Workflow Diagram Data Sources ⟶⟶ Python/SQL Processing ⟶⟶ Spark Transformation ⟶⟶ Airflow/Dagster Pipelines ⟶⟶ Cloud Warehouse ⟶⟶ dbt Modeling ⟶⟶ Data Quality & Monitoring Key Highlights ✔ Production-ready data pipelines using Python, SQL, Apache Spark, and modern orchestration tools. ✔ ETL/ELT workflows designed for reliability, scalability, and maintainability. ✔ Airflow, Dagster, or Prefect for scheduling, dependencies, retries, and pipeline monitoring. ✔ dbt-based transformations with clean, modular data models and documentation. ✔ Experience-ready architecture for Snowflake, BigQuery, Redshift, or Databricks environments. ✔ Cloud integration across AWS, Azure, or GCP with secure and scalable deployment practices. ✔ Git-based development with testing, CI/CD, Docker, and production deployment workflows. ✔ Strong focus on data quality, validation, observability, and failure recovery. ✔ Clean documentation and clear communication for effective remote collaboration. Best Regards, Asad Data Engineer | Python | SQL | Spark | Cloud Data Platforms

@Jeeldhola01

Hello, I have strong hands-on experience in Data Engineering, with skills in Python, SQL, and Apache Spark for building solid data pipelines. I have worked with tools like Airflow, dbt, and cloud platforms such as AWS, Azure, and GCP, plus data warehouses like Snowflake, BigQuery, and Databricks. I understand data modeling, Git workflows, and production pipeline support well. I can join your remote team and easily overlap with US business hours. My English communication is clear and strong, great for teamwork across time zones. Let's connect to discuss the role, timelines, and how I can add value to your project.

@rehanahmad9766

Hiie Sir, I read your brief for a Data Engineer – Remote Contract. You're looking for a system that doesn't crash when production data pipelines, distributed processing, and international workloads run at scale. We're a development agency with 7+ years in the software space. We've built production-grade data pipelines using Python, SQL, Spark, cloud data platforms, orchestration, and modern data modeling. Here's what most freelancers won't tell you: building data pipelines is easy. Building reliable Spark workflows, orchestration, cloud warehouse integrations, data quality, modeling, and production observability — that's where projects actually live or die. Market is full of cheaper quotes or faster promises. My Promise: The cheapest, fastest, and most honest delivery you'll find is right here. Drop me a msg… Let's talk about your workflow for 10 minutes. No pitch, just QA. Genuinely, Khan Rehan Sr. Backend Developer, Small Gear Inc. (Python, Data Engineering & Cloud Data Platforms) P.S. : Python, SQL, Azure, AWS, BigQuery, Spark, Snowflake, Databricks, Hadoop, Airflow, dbt, Kafka, Docker, Kubernetes, Terraform, CI/CD — battle-tested stack.

@mert422

I understand you need an experienced Data Engineer for a remote contract project. I can deliver a quick demo of a data pipeline using Python and Apache Spark within 24 hours to verify my skills. Please message me immediately to receive your demo and discuss the project details. Muhammet Karakurt

@mohamedaminea1

Hi ? This looks like the kind of data engineering work I enjoy—building pipelines that run reliably at 2 AM so nobody has to wake up at 2 AM. ? I can contribute across the modern data stack, including: • Python + SQL for ETL/ELT and data processing • Apache Spark for distributed workloads • Airflow/Prefect-style orchestration • dbt for transformations, testing, and modeling • Snowflake/BigQuery/Databricks-style warehouse architectures • AWS/Azure cloud environments • Git, Docker, CI/CD, monitoring, and production pipeline debugging I focus on more than getting a pipeline to “work.” It should be maintainable, observable, idempotent where appropriate, tested, and able to fail loudly instead of silently corrupting Tuesday’s dashboard. I’m comfortable collaborating remotely, documenting technical decisions, and overlapping with US business hours. Happy to discuss your current architecture, data volume, orchestration stack, and the first pipeline you’d like me to own. Thanks!

@nandezgarcia

Hi, I can help with your data engineering needs. I have strong experience with Python, SQL, data pipelines and ETL processes. I can assist with data modeling, pipeline development and optimization. I can start with a discovery phase to understand your current architecture and then propose a concrete implementation plan.

@AnmolChauhan001

As an experienced Big Data Engineer with nearly 5 years of hands-on experience in Azure, PySpark, and Databricks, I can design and implement your pipeline with a focus on scale, clean data modeling, and automated deployment. Azure & Databricks Expertise: Extensive background architecting Medallion Architecture (Bronze, Silver, Gold) for seamless ingestion and analytics. PySpark & SQL Performance: Deep experience writing high-performance PySpark scripts and optimizing complex SQL queries for massive datasets. Infrastructure & CI/CD: Proficient in automating deployments using Terraform and setting up robust CI/CD workflows with GitHub. Full Data Lifecycle: Skilled in tracking health via Grafana, handling end-to-end data management, and integrating with Power BI for reporting.

@prachia77

We’re interested in supporting this remote Data Engineering contract as a technical team from Webix Infotech. We can provide developers with strong experience in Python, SQL, data pipelines, cloud platforms and backend systems. Our team can work with technologies such as Apache Spark, Airflow, dbt, Databricks, Snowflake, BigQuery and AWS/Azure, depending on the project requirements. We understand this is a production-focused role involving data modeling, pipeline development, Git workflows and reliable ETL/ELT processes rather than just short-term scripting. We can also provide ongoing technical support and maintain consistent availability for international collaboration and US-hour overlap. Our approach would be to first understand your existing architecture, data sources, pipeline requirements and cloud environment, then align the right developer from our team with the project. We’re available to discuss the contract, required experience and expected monthly engagement. Best Regards, Prachi Webix Infotech

@DeanSaliegh

I can help you build robust data pipelines that ensure seamless data flow and analytics for your international client. The focus on modern tools like Snowflake and Apache Spark caught my eye, as they are crucial for scalable solutions. I have done similar work: Modern Real Estate Investment Website - [Link]. My approach combines strong Python and SQL skills with hands-on experience in Airflow and dbt, enabling me to craft efficient and reliable data workflows. Let’s chat about how I can support your project and bring it to the next level. At the very least, you'll get a free consultation to discuss the best approach. Regards, Dean