Freelancers using Apache Airflow in Boston
Freelancers using Apache Airflow in Boston
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El Mehdi El Wafi
pro
Morocco
Linux VPS SysAdmin AWS & Oracle Cloud Architect | Terraform
1x
Hired
12
Followers
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Linux VPS SysAdmin AWS & Oracle Cloud Architect | Terraform
1
92% Cost OFF of EC2 Airflow/DBT Workers using Lambda
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17
$12K+ earned
3
DevOps/Cloud & DataOps maintainer
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35
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🛠️ DevOps Tips 🛠️ If your GitHub workflows or jobs are failing due to jobs concurrently accessing and/or modifying shared resources, You can control execution at the workflow or job levels using the concurrency. Jobs/Workflows in the same are prohibited from running at the same time, and you can cancel any jobs/workflow if you trigger another one. Groups let you define compartments in which you don't want concurrent workflows running. They can be organized however you like. I find that using them in separate environments is a great practice. Cancel-in-progress: specifies if the old running job/workflow needs to shut down. Read more in docs: https://docs.github.com/en/actions/how-tos/write-workflows/choose-when-workflows-run/control-workflow-concurrency
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625
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Enterprise VM Template for Proxmox VPS
0
11
Apache Airflow
(2)
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ADEWUNMI OLUWASEYI
Lagos, Nigeria
Expert in building an efficient and scalable data pipeline
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Expert in building an efficient and scalable data pipeline
0
Scalable E-commerce Big Data Platform for BuildItAll
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5
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BeejanTech Analytics Platform Development
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5
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Offensive Card Booking Tracker for Football Club
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4
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AWS Infrastructure Provisioning with Terraform
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4
Apache Airflow
(3)
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Abhishek Jha
United Arab Emirates
Analytics Engineer | Snowflake, Airflow, dbt
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Analytics Engineer | Snowflake, Airflow, dbt
0
Reverse ETL: Warehouse Data Back to Sales Tools
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6
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Data Quality Framework: 62% to 99% Accuracy
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5
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Real-Time Analytics: 48hr Latency to 90 Seconds
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9
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I Build Production-Grade Data Pipelines (ETL, Medallion, Snowflake, dbt) Messy data → clean, trusted analytics in ~2 weeks.
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78
Apache Airflow
(8)
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Aishwary Dhare
pro
Bengaluru, India
Full Stack Rapid Prototyping – Vision to Product in Weeks 🚀
5.0
Rating
7
Followers
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Full Stack Rapid Prototyping – Vision to Product in Weeks 🚀
0
Migration of ETL Pipelines to Apache Airflow
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16
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Global FinTech Development for MishiPay
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11
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Development of PayLater & PayLater Business Apps
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21
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Development and Launch of MishiPay Self-checkout Kiosks
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11
Apache Airflow
(1)
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Miruna Popa
Berlin, Germany
Product Analytics Consultant
New to Contra
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Product Analytics Consultant
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* Delivered on a number of projects within the Service Product Line, projects including: * Rider Customer Chat * Customer Agent Chat * Fraud detection (Exploit) * Event Tracking system (internal solution for tracking) * First analyst within projects, set up from scratch all of the tracking, AB Testing and setting up an analytics mentality, North star metrics, monitoring and troubleshooting * Led cross functional discussions among Analysts, Engineers, Product managers and Operations analysts, which moved the needle further. * Brought in a more collaborative mentality among analysts, and set up weekly sharing sessions, as well as informal follow ups. This in the end created more trust, a happier team and better quality of deliverables for stakeholders.
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* Started off as an intern and grew to be a Data Scientist * Prepared ETLs for better ingestion of stream data * Worked cross functionally together with Product Managers and Engineers on delivering features, both for the B2C and B2B part of the business * Performance measuring of Computer Vision models by working closely with the Computer Vision team Set up internal emailing system that would automatically deliver reports and raw data inside the company for better performance - reducing waiting times for the Operations team and unblocking them to best achieve their goals
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* Main point of contact for Data Science aspects for Candy Crush Jelly Saga , third game of the Candy Crush Franchise * Delivered important features together with a cross-functional team (such as Player vs. Player, Ads, Buddies) instrumental to achieving strategic goals within the game and at an organisation wide level * Responsible of all AB Tests in the game: AB test design, open questions in pre-production, release monitoring, final feature analysis * Made impactful recommendations on how to improve the game, by aligning with key stakeholders on strategic goals * Advocate for mentoring and data transparency: held mentoring sessions with Junior colleagues as well as with the team on the tools they can use to independently make data driven decisions
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Main analyst for the Supply Loyalty program, maintaining engagement of our main supply source in the Rides Vertical. Interim Lead for the Supply Analytics team for 6 months, during which i’ve provided valuable guidance to my peers and regular 1-1s, clarifying ambiguous requirements, delegating functional tasks In my time as interim lead, i have also brought in Focus days as part of a 20% discovery time agreement. I have also introduced a review system for our work in order to increase the quality of our output End-to-end feature development, from recognising high stakes opportunities to delivering in-app experiences through data modelling. Cross functional collaboration, with stakeholders such as Group Product Managers, Engineering Managers and functional analytics leads Personal roadmap management guaranteeing on time delivery, completely autonomous Mentoring of other colleagues during organisational changes, such as highlighting opportunities that could benefit both org and individual contributors
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53
Apache Airflow
(1)
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Umar Shaikh
Pune, India
Data Scientist, Backend Engineer, Data Analyst
10
Followers
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Data Scientist, Backend Engineer, Data Analyst
2
Proud to share that I’ve earned the Oracle Cloud Infrastructure (OCI) 2025 Certified Data Science Professional certification (https://tinyurl.com/dsmlaidl) — issued by Oracle. This certification validates my expertise in Machine Learning (ML) | Data Science | Artificial Intelligence (AI) | Cloud Computing, showcasing my ability to design, build, deploy, and manage end-to-end ML solutions using OCI Data Science and Oracle AI Services. 💡 Core Expertise: 🔹 Scalable ML pipelines on OCI Data Science 🔹 AI, MLOps, and Cloud best practices for model optimization 🔹 Leveraging OCI Data Flow, Data Catalog, and AI Services for automation 🔹 Skilled in Python | TensorFlow | Scikit-learn | OCI SDKs for production-grade workflows 💪 Passionate about applying ML | Data Science | AI | Cloud Innovation to drive real business transformation.
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main_palmer_penguin_EDA_2024-project
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16
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main_palmer_penguin_EDA_2024-project
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11
1
Fraud_Transaction_Detection-Fraud_Finder_ID12254…
1
17
Apache Airflow
(1)
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ANIMESH SINGH
Delhi, India
Data & AI Engineer
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Data & AI Engineer
3
Problem: Many organizations still process invoices manually by reading PDF documents and entering key details (invoice number, vendor, amount, etc.) into systems. This process is slow, error-prone, and difficult to scale, and it also makes it harder to detect duplicate invoices or incorrect totals. Solution: This project builds an automated invoice processing pipeline that converts uploaded invoice PDFs into structured data. It uses OCR to extract text, LLMs to identify invoice fields, validation checks to ensure correctness, and Kafka-based event streaming to manage the processing pipeline. The extracted data is stored in PostgreSQL and visualized through a dashboard, enabling faster, scalable, and more reliable invoice processing.
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Problem Statement Urban traffic management systems lack real-time, integrated data combining traffic conditions with weather patterns. This results in poor routing decisions, delayed emergency responses, and inefficient traffic flow management. Solution Developed a comprehensive real-time ETL pipeline that integrates traffic APIs and weather data sources, processes millions of data points, and delivers actionable insights through interactive dashboards for traffic management and route optimization.
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A fully Dockerized real-time IoT ETL pipeline that simulates device telemetry, processes events through MQTT and Kafka, orchestrates workflows with Airflow, and delivers real-time alerts and insights to CRM systems with monitoring via Grafana and Loki.
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A fully local RAG pipeline that transforms your PDFs into a queryable knowledge base using FAISS vector search and Ollama LLMs. No cloud, no API keys - just private, grounded document intelligence running entirely on your machine.
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61
Apache Airflow
(3)
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Rishi Barapatre
Ahmedabad, India
I build AI chatbots that save small businesses hours
New to Contra
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I build AI chatbots that save small businesses hours
0
Automated ETL Pipeline: Weather & Air Quality Data Warehouse
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Multilingual AI Sales Agent for Lead Qualification
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1
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RAG Chatbot That Answers From Your Docs
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0
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Fine-Tuned LLM: Messy Text to Clean JSON
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0
Apache Airflow
(1)
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