Hire the Best Data Engineers
Faisalabad, Pakistan
Are you struggling to reach the right 𝐃𝐞𝐜𝐢𝐬𝐢𝐨𝐧-𝐌𝐚𝐤𝐞𝐫𝐬? I help B2B businesses connect with 𝗖𝗘𝗢𝘀, 𝗙𝗼𝘂𝗻𝗱𝗲𝗿𝘀, 𝗖𝗠𝗢'𝗦, 𝗠𝗮𝗿𝗸𝗲𝘁𝗶𝗻𝗴 𝗠𝗮𝗻𝗮𝗴𝗲𝗿𝘀 𝗮𝗻𝗱 𝗗𝗶𝗿𝗲𝗰𝘁𝗼𝗿𝘀, 𝗦𝗮𝗹𝗲𝘀 𝗠𝗮𝗻𝗮𝗴𝗲𝗿𝘀, and key executives who are actually ready to buy. My name is 𝐇𝐚𝐫𝐢𝐬 𝐀𝐥𝐢 and I specialize in 𝐁𝟐𝐁 𝐋𝐞𝐚𝐝 𝐆𝐞𝐧𝐞𝐫𝐚𝐭𝐢𝐨𝐧 with 𝟰+ 𝘆𝗲𝗮𝗿𝘀 of experience delivering high-quality, verified business leads that drive real sales conversations. What I Deliver: ✅ Targeted B2B Company & Contact Research ✅ Decision Maker Identification (CEO, CFO, VP, Manager) ✅ Verified Business Emails & LinkedIn Profiles ✅ Industry & Niche Specific Lead Lists ✅ LinkedIn Outreach & Connection Campaigns ✅ Cold Email List Building ✅ CRM Data Upload (HubSpot, Salesforce, Zoho) My Research Process: 🔍 Identify your ideal customer profile (ICP) 🔍 Find companies matching your target criteria 🔍 Locate key decision makers 🔍 Verify emails & contact details 🔍 Deliver clean, ready-to-use data Tools I Use: LinkedIn Sales Navigator | Apollo,io | Hunter,io | Snov,io | ZoomInfo | Clearbit | Crunchbase Industries I Work With: ✔ SaaS & Tech Companies ✔ Marketing & Advertising Agencies ✔ Real Estate & Construction ✔ Healthcare & Medical ✔ Finance & Consulting ✔ E-commerce & Retail Why Choose Me: ❌ No random, unverified lists ❌ No fake or bounced emails ✅ Only manual, verified, targeted leads ✅ Leads that match your exact ICP ✅ Fast turnaround with clear communication 📌 4+ Years B2B Experience 📌 Verified & Accurate Data — Guaranteed 📌 Ready to scale your outreach immediately Let's talk about your target market. Send me a message and let's build your B2B pipeline today! 🚀
- Lead Generation
- B2B Lead Generation
- LinkedIn Lead Generation
- Social Media Lead Generation
- Real Estate Lead Generation
- Data Entry
- Data Mining
- Data Scraping
- Data Extraction
- Contact Info Research
- List Building
- CRM Software
- Email List
- Market Research
- Web Scraping
- Virtual Assistance
- Data Annotation
- Data Labeling
- Administrative Support
- English
Mahdia, Tunisia
Greetings! I'm Salah Sammari, a dedicated Data Scientist with a focus on Natural Language Processing. Having accumulated over two years of hands-on experience in the realm of AI and machine learning, I'm reaching out to offer my expertise for your AI-driven endeavors. Professional Snapshot: My journey began with a solid foundation in Computer Science Engineering from the Higher School of Engineers Esprims in Tunisia. Over the past two years, I've been privileged to work with distinguished organizations such as DNEXT Intelligence SA and UBIAI. In these roles, I've not only implemented advanced NLP solutions but also successfully navigated challenges in trading platform optimization and extended data science training to budding enthusiasts. Core Competencies: NLP & Machine Learning: Expertise in various techniques ranging from sentiment analysis, topic modeling to Named Entity Recognition (NER). I've extensively worked with transformer models such as GPT, BERT, and LayoutLM. Programming & Tools: Proficient in Python and SQL (Postgres) with a keen understanding of data science libraries like Pandas-Numpy, Matplotlib-Seaborn, and Scikit-learn. My skill set also includes cloud platforms like AWS and Snowflake. Project Highlights: From developing AI-driven solutions for content filtering and recommendation engines to building transformer-based chatbots and leveraging OCR techniques, I've overseen multiple projects that required innovative problem-solving and rigorous model fine-tuning. Collaboration & Training: My cross-functional collaboration experience ensures smooth project executions. Additionally, as a Data Science Trainer at Ruspina Training Center, I've mentored over 150 students in Python, machine learning, and NLP. What Drives Me: I thrive on challenges and continually seek opportunities to apply my skills in diverse scenarios. My rank as a Kaggle Master, standing in the top 1%, speaks volumes about my passion for pushing the boundaries of what AI can achieve. The blend of rigorous academia, practical applications, and my incessant drive to learn has shaped my holistic approach to problem-solving.
- Python
- Deep Learning
- Data Science
- Machine Learning Model
- Data Science Consultation
- Data Visualization
- Machine Learning
- Data Analysis
- Natural Language Processing
- Transformer Model
- Chatbot
- GPT-3
- LLM Prompt Engineering
- Hugging Face
- Recommendation System
Surigao, Philippines
Do you have 𝙧𝙚𝙨𝙚𝙖𝙧𝙘𝙝 𝙤𝙧 𝙙𝙖𝙩𝙖 𝙩𝙖𝙨𝙠𝙨 𝙨𝙞𝙩𝙩𝙞𝙣𝙜 𝙤𝙣 𝙮𝙤𝙪𝙧 𝙡𝙞𝙨𝙩 that you just don’t have time to finish? ⏰ Save time by letting me handle your research tasks. 📊 Clean data entry with accuracy & high quality. ✅ Reliable results you can actually use 🚀 Focus on scaling your business while I handle the details. How I Can Help Your Business 👇 🔥 𝐁𝟐𝐁 𝐋𝐞𝐚𝐝 𝐆𝐞𝐧𝐞𝐫𝐚𝐭𝐢𝐨𝐧 & 𝐂𝐨𝐧𝐭𝐚𝐜𝐭 𝐑𝐞𝐬𝐞𝐚𝐫𝐜𝐡 ◆ I can research and compile targeted prospect lists with verified details such as business names, websites, emails, phone numbers, locations, LinkedIn profiles, company info, and decision-maker details. 🔥 𝐃𝐚𝐭𝐚 𝐑𝐞𝐬𝐞𝐚𝐫𝐜𝐡 & 𝐀𝐧𝐚𝐥𝐲𝐬𝐢𝐬 ◆ I help collect, organize, and review business data so clients can make better decisions. This includes market research, product research, competitor research, location research, and online information gathering. 🔥 𝐒𝐨𝐜𝐢𝐚𝐥 𝐌𝐞𝐝𝐢𝐚 𝐑𝐞𝐬𝐞𝐚𝐫𝐜𝐡 & 𝐌𝐚𝐧𝐚𝐠𝐞𝐦𝐞𝐧𝐭 𝐒𝐮𝐩𝐩𝐨𝐫𝐭 ◆ Need help researching influencers, social media pages, content ideas, hashtags, trends, or potential leads from platforms? I can organize the data clearly and support your social media workflow. 🔥 𝐀𝐜𝐜𝐮𝐫𝐚𝐭𝐞 𝐃𝐚𝐭𝐚 𝐄𝐧𝐭𝐫𝐲 & 𝐃𝐚𝐭𝐚 𝐂𝐨𝐥𝐥𝐞𝐜𝐭𝐢𝐨𝐧 ◆ I can manage repetitive but important tasks such as entering information into spreadsheets, cleaning data, formatting lists, updating records, and keeping files organized. 🔥 𝐂𝐚𝐧𝐯𝐚 𝐒𝐮𝐩𝐩𝐨𝐫𝐭 𝐟𝐨𝐫 𝐑𝐞𝐞𝐥𝐬, 𝐂𝐚𝐫𝐨𝐮𝐬𝐞𝐥𝐬 & 𝐂𝐨𝐧𝐭𝐞𝐧𝐭 𝐈𝐝𝐞𝐚𝐬 ◆ I can help with Canva-based content support, including simple graphics, carousel ideas, reel support, and organized content research for social media posts. 🔥 𝐄𝐦𝐚𝐢𝐥 𝐕𝐞𝐫𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧 & 𝐎𝐧𝐥𝐢𝐧𝐞 𝐑𝐞𝐬𝐞𝐚𝐫𝐜𝐡 ◆ I can help find and verify emails, websites, business details, contact pages, LinkedIn profiles, and other online information needed for outreach or business development. 𝙒𝙝𝙮 𝙒𝙤𝙧𝙠 𝙒𝙞𝙩𝙝 𝙈𝙚 ⭐ 100% Job Success ⭐ Top Rated freelancer ⭐ 5-star client feedback ⭐ Detail-oriented and reliable ⭐ Clear communicator ⭐ Fast learner and easy to work with ⭐ Focused on accurate, clean, and useful data 🎯𝐏𝐨𝐰𝐞𝐫𝐟𝐮𝐥 𝐑𝐞𝐬𝐞𝐚𝐫𝐜𝐡 𝐓𝐨𝐨𝐥𝐬 𝐈 𝐔𝐬𝐞 ➤ Google Search ➤ Google Maps ➤ LinkedIn ➤ LinkedIn Sales Navigator ➤ Apollo ➤ Hunter ➤ ContactOut ➤ Verifalia ➤ NeverBounce ➤ Google Sheets ➤ Microsoft Excel ➤ Google Docs ➤ Canva ➤ CapCut ➤ ChatGPT ➤ Grok ➤ Gemini I am focused, accurate, and efficient, committed to completing every task flawlessly. Let's connect and make a great work together!
- Data Entry
- Lead Generation
- Company Research
- Online Research
- Email List
- Data Extraction
- Data Scraping
- Web Scraping
- Data Collection
- B2B Lead Generation
- Conduct Research
- Prospect Research
- Email Sourcing
- LinkedIn Lead Generation
- Product Research
- Canva
- Social Media Design
- Google Sheets
- Market Research
- Contact List
Dhaka, Bangladesh
Hi, I’m Mohini Sultana. I’m skilled Data Annotator with 5+ years of experience in image/video labeling, AI data processing, Satellite Image Annotator, virtual assistance, and data entry. I’m reliable, deadline-driven, and ready to work across any time zone. I specialize in prioritizing tasks and solving problems efficiently to ensure high-quality results. Common Types of Annotations: * Bounding Boxes – Draw rectangles around objects. * Polygon Annotation – Outline the exact shape of objects. * Semantic Segmentation – Label every pixel in an image with a class (e.g., road, car, person). * Instance Segmentation – Like semantic, but distinguishes between object instances * Keypoint Annotation – Mark specific points (e.g., facial landmarks, human joints). * Classification – Assign a label to the whole image (e.g., “cat” or “dog”). * Object Counting – Count how many of a specific object are present. * Lane or Line Annotation – For road detection, lane marking. List of the tools that I learned and used: ✔️ CVAT ✔️ Roboflow ✔️ SuperAnnotate ✔️ Darwin V7 ✔️ Supervisely ✔️ Labelbox ✔️ Labelimg ✔️ Labelme ✔️Scale Pro ✔️Dataloop Ai ✔️QGIS ✔️ Canva ✔️ Filmora ✔️Photoshop ✔️Canva Skills: - Prepares a dataset for computer vision or machine learning and models. - AI Image annotation/Video Annotation - AI Data Processing - AI Annotation format converting - Image Masking - Image Segmentation - Categorization - Fact-Checking Annotation - Data entry - Virtual assistant - Data scraping While I am grateful for the opportunities afforded to me in my prior position, I am ready to embark on a new career path that offers new challenges for me to put my skills to use. #Data annotation #image Annotation #Data Labeling #Data Annotation Specialists #Annotation Specialists #Cvat #Superannotate #Image Segmentation #Video Annotation #Roboflow #Data Annotator I'm a very competitive person and a fast learner. Rest assured, I provide high-quality output, and also I can do tasks as fast and accurately as possible. Your project's success starts with the right data annotation, and I am here to provide just that.
- Image Annotation
- Video Annotation
- Data Annotation
- Data Labeling
- Quality Assurance
- Image Segmentation
- Data Processing
- Data Entry
- Lead Generation
- Virtual Assistance
- Copy & Paste
- B2B Lead Generation
- CVAT
- Roboflow
- SuperAnnotate
Trier, Germany
✨ Upwork Expert-Vetted & 𝐓𝐨𝐩 𝐫𝐚𝐭𝐞𝐝 𝐩𝐥𝐮𝐬 (Top 1%) ✨ 100 % Job Success in large Projects Senior Data Scientist with a combined 6+ years of experience [𝐇𝐞𝐚𝐥𝐭𝐡𝐜𝐚𝐫𝐞, 𝐒𝐨𝐜𝐢𝐚𝐥 𝐒𝐞𝐜𝐮𝐫𝐢𝐭𝐲, 𝐓𝐨𝐮𝐫𝐢𝐬𝐦, 𝐅𝐢𝐧𝐭𝐞𝐜𝐡 Industries] I help businesses maximize their growth potential through data-driven solutions and assist Tech teams to build robust ML solutions from real-world Sensors and Time Series data. I specialize in Feature Engineering, Event Detection, and Predictive Modeling, with a strong focus on model reliability and uncertainty estimation. I also deliver clear Technical Reports, Presentations and decision focused documentation that bridge research and product. EXPERTISE - Research | Custom Technical Reports (Text + Figures + Interpretation) | Code/Scientific Documentation. - Data Analytics: Data Cleaning, Exploratory Analysis, and actionable Insight generation. - Designing, Training and Evaluating AI/Machine Learning models. - Collecting, Cleaning and Managing data and databases. - Developing the data and result into a format easily representable to other employees, investors, and other researchers. SKILLSET ✅ Time Series Analysis (Sensors/ Signals, Accelerometer ...) ✅ Biological Signals: Heart and Breathing, Temperature, Muscle activity, Brain activity, Blood Pressure, Oxygen levels and Body Composition. - Trend/ Behavioral Analysis and Profiling. - IoT/Sensor Data Diagnostics - Anomaly Detection - Exploratory Data Analysis - Scoping sessions and Data‑Quality assessments ✅ Python (Pandas–Scikit-learn–Numpy–Scipy, Seaborn–Keras–Pytorch–TensorFlow). ✅ R (ggplot2–dplyr–tidyr –caret–Shiny–Tidyquant). ✅ Machine Learning Algorithms (PCA, K-means, Random Forest, XGboost, Logistic Regression, SVM, etc..). ✅ Deep Learning (Neural Networks, CNN, RNN, ...) also the tools: - SQL/No-SQL: MongoDB, MySQL. - Tableau | Power BI. - MATLAB | R-studio. - Git - C/C++ I'm adaptable, quick, and reliable, with a sharp eye for details and excellent communication skills (6 languages). I'm eager to help you solve any data science challenges you might have. ------------------------------------------------------------------------------------------------------------------------- Testimonials from some of my clients: ✨ "Working with Faten was effortless. She is dependable, while also incredibly collaborative. Her dedication to work and ability to deliver consistently on-time and beyond expectations render her invaluable for any project. I highly recommend Faten to anyone seeking a skilled, reliable and communicative Machine Learning Engineer and or Data Scientist for their next initiative." ✨"Faten is very professional - prompt feedback, clear communication, and easy to work with. Would recommend working with Faten on ANY project!" ✨"It was an absolute pleasure to work with Faten. She is super clear on communication and has a creative curiosity about all projects. She is a brilliant soundboard and fits into the projects, regardless of where she is asked to assist. She always adds value. I will recommend her without reservation"
- Python
- Data Science
- R
- Machine Learning
- Classification
- Deep Learning
- Feature Extraction
- Statistical Analysis
- Neural Network
- Statistics
- Time Series Analysis
- Time Series Forecasting
- Modeling
- Wearables Software
- Sensor
- Data Visualization
- Data Analysis
- Data Science Consultation
- Report
- Retrieval Augmented Generation
Rawalpindi, Pakistan
Data is as valuable as the decisions it enables. Is your leadership team waiting weeks for reports? Are your data pipelines constantly breaking, or is your cloud spend spiraling out of control? I don't just "write ETL", I build the scalable, automated engines that turn raw, messy data into real-time business intelligence. With over 6,000+ hours on Upwork and a 100% Job Success Score, I help enterprises move from manual data chaos to a streamlined, modern data stack. My Core Focus: - Microsoft Fabric: End-to-end implementation (OneLake, Data Factory, Lakehouse/Warehouse). - Databricks: Building robust Medallion architectures using Spark, Delta Lake, and Unity Catalog. - Automated ETL/ELT: Designing resilient pipelines with Airflow, Azure Data Factory, and Python. - Enterprise BI: High-performance Power BI dashboards using Direct Lake and advanced DAX. Why Clients Choose Me: I bridge the gap between technical complexity and business ROI. Whether you are migrating from legacy SQL servers to the cloud or optimizing a complex Databricks environment, I focus on two things: Performance and Clarity. Technical Ecosystem: - Languages: Python, SQL, PySpark, DAX - Platforms: Microsoft Fabric, Azure Synapse, Databricks, Snowflake - Tools: Airflow, ADF, Power BI, Tableau, PostgreSQL/MySQL Ready to transform your data infrastructure into a strategic asset? Click the "Message" or "Book Consultation" button, and let’s discuss your architecture.
- Data Engineering
- Python
- Data Warehousing & ETL Software
- Microsoft Azure SQL Database
- Microsoft SQL Server
- Database
- Data Warehousing
- ETL
- ETL Pipeline
- Data Ingestion
- Data Migration
- SQL
- Microsoft Power BI
- Microsoft Power BI Data Visualization
- Data Modeling
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Data engineer hiring guide
In today's digital landscape, businesses generate massive amounts of data. To transform this raw data into valuable insights, companies need robust, scalable infrastructure. Data engineers are indispensable technical experts who build the pipelines, warehouses, and systems allowing data scientists to utilize data effectively.
What does a data engineer do?
Data engineers build and maintain the infrastructure making data accessible across your organization. While data scientists analyze information to develop insights, data engineers create the systems enabling that analysis. They design, construct, test, and maintain scalable data management systems.
Their primary focus is establishing a consistent data flow for downstream analysis by building extract, transform, load (ETL) pipelines, setting up data warehouses, and ensuring data quality. Without this foundation, data scientists would spend their time cleaning raw data instead of generating insights.
Day-to-day responsibilities for data engineers typically include:
Pipeline construction. Creating automated workflows that move data from various sources to a centralized destination
Database management. Designing and maintaining SQL and NoSQL databases to ensure efficiency and reliability
Infrastructure scaling. Utilizing cloud platforms like AWS, Google Cloud, or Azure to scale storage and processing power as data volumes grow
Data cleaning. Implementing scripts and tools to detect and correct corrupt or inaccurate records
How to hire a data engineer on Upwork
Finding the right data engineer requires a structured approach to ensure they possess both the technical skills and industry context necessary for your project. Follow these steps to hire top data engineering talent on Upwork.
Step 1: Craft a targeted job post
Your job post is the first point of contact and directly influences applicant quality. A well-crafted posting helps qualified data engineers quickly understand if their expertise aligns with your needs.
Start with a clear job post outlining your project goals, required technical skills, and expected deliverables.
Detail the scope of work, including specific deliverables like building scalable infrastructure or ETL pipeline development.
Specify required technical skills (e.g., Apache Spark, Kafka, Python, SQL, AWS, Azure) and mention relevant industry experience.
Set clear budget expectations and timelines.
Streamline this step by using Upwork's Job Post Generator, powered by Uma™, Upwork's Mindful AI, to draft a customizable post for your review.
Step 2: Filter and evaluate candidates
A systematic evaluation approach ensures you invest interview time only with promising applicants. Prioritize candidates whose technical backgrounds demonstrate success with challenges similar to yours.
Use Upwork's filters (expertise level, hourly rate, location, and specialized skills) to narrow your search.
Assess technical fit by looking for data engineers with experience in your specific technology stack and data infrastructure needs.
Review portfolios for relevant work, such as building ETL pipelines, implementing data warehouses, or working with big data tools.
Check client feedback and read reviews to identify reliable communicators with a track record of delivering quality work on time.
Step 3: Interview your top choices
Interviews let you assess how candidates approach real-world problems and if their working style complements your team. Use this stage to gauge technical depth and collaboration ability.
Test communication skills to ensure the engineer can clearly explain complex concepts to nontechnical stakeholders.
Ask candidates to walk through a complex infrastructure they designed, and present a hypothetical challenge relevant to your company's needs.
Evaluate documentation practices and workflow for knowledge transfer, which is vital for long-term maintenance.
Review database programmer interview questions and AWS developer interview questions to set up a custom slate of questions to use to assess technical expertise.
Step 4: Agree on scope and begin work
Establishing mutual understanding of project parameters before work begins sets the foundation for success. Documenting expectations protects both parties and creates accountability.
Clearly define the project scope, deliverables, and payment terms in a contract agreement.
Choose between an hourly contract for ongoing flexibility or a fixed-price model for finite budget and deliverables.
Set clear milestones for key stages like pipeline design, implementation, and testing.
Use Upwork's messaging and contract workroom to enhance communication; identity verification, Hourly Payment Protection, and time tracking provide security for both parties.
Upwork is not affiliated with and does not sponsor or endorse any of the tools or services discussed in this article. These tools and services are provided only as potential options, and each reader and company should take the time needed to adequately analyze and determine the tools or services that would best fit their specific needs and situation.
The rates and information provided in this article are based on current data and industry sources available at the time of publication. Freelance rates can vary depending on factors such as experience, location, project scope, and market conditions. Readers are encouraged to conduct their own research to confirm current rates and trends, as this information may change over time.
How much does hiring a data engineer cost?
On Upwork, data engineer rates are similar to those for data analysts, with a range from $20-$50 per hour. Hiring costs vary based on the engineer’s experience and specialization and the project scope. For example, specialists in distributed systems or machine learning operations command higher rates. For additional information on costs for related roles, see Upwork's hourly rates guide.
When budgeting, consider these typical project cost ranges for data engineering activities:
Data pipeline setup
$1,500-$5,000 /project
- Single ETL pipeline
- Basic warehouse setup
- Schema design
Data infrastructure build
$5,000-$15,000 /project
- Multisource integration
- Automated workflows
- Testing
- Optimization
Enterprise data architecture
$15,000+ /project
- Distributed systems design
- Cloud migration strategy
- Complex system integrations
Ongoing data maintenance
$2,000-$8,000 /month
- Performance monitoring
- Pipeline optimization
- Regular updates
- Troubleshooting
Data strategy consulting
$10,000-$25,000+ /project
- Data roadmap development
- Governance framework
- Technology stack evaluation
FAQs about data engineers
Frequently asked questions
Is hiring a data engineer worth it?
Yes, hiring a data engineer is worth it because the professional can increase data reliability, scalability, and accessibility to support better decision-making. They build the pipelines and infrastructure ensuring data is accurate and usable. Once multiple sources require integration or data quality issues affect decisions, the efficiency gained from professional data engineering typically justifies the cost.
What’s the difference between a data engineer and a data scientist?
While data engineer and data scientist roles overlap, they have distinct focuses. A data engineer designs, constructs, and maintains data systems, ensuring data is reliable, accessible, and secure. A data scientist uses that prepared data alongside advanced statistics and machine learning to solve business problems. Think of the data engineer as the one building the race car, and the data scientist as the driver winning the race.
What are the most critical skills for a data engineer?
Key skill requirements for a data engineer include proficiency in Python or Java, deep SQL knowledge (see these SQL developer interview questions), experience with big data tools like Hadoop or Spark, and familiarity with cloud services (AWS, Google Cloud, Azure). Understanding data warehousing and containerization tools like Docker and Kubernetes is also increasingly important.
Do I need a data engineer if I already have a database administrator?
Yes, even if you already have a database administrator (DBA), your organization can benefit from hiring a data engineer. A DBA focuses on the health, security, and maintenance of specific databases, while a data engineer handles the movement, transformation, and integration of data across systems. Building pipelines that pull data from CRMs, analytics, and financial software into a unified data warehouse requires a data engineer's specialized skills.
Can data engineers work effectively remotely?
Data engineering is well-suited for remote work. Most infrastructure resides in cloud environments that are securely accessible from anywhere. With proper access to code repositories, cloud platforms, and collaboration tools, a freelance data engineer is just as effective working remotely as on-site — often at a more competitive rate due to access to the global talent pool on platforms like Upwork.
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