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
Khulna, Bangladesh
Hi, I’m Tazmir Hossain, and I specialize in helping businesses scale through 𝗵𝗶𝗴𝗵-𝗾𝘂𝗮𝗹𝗶𝘁𝘆 𝗹𝗲𝗮𝗱 𝗴𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝗼𝗻 𝗮𝗻𝗱 𝗱𝗮𝘁𝗮 𝗺𝗶𝗻𝗶𝗻𝗴 𝘀𝗲𝗿𝘃𝗶𝗰𝗲𝘀. With over 𝟴 𝘆𝗲𝗮𝗿𝘀 𝗼𝗳 𝗲𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲 and a 𝟗𝟎% 𝗝𝗼𝗯 𝗦𝘂𝗰𝗰𝗲𝘀𝘀 𝗥𝗮𝘁𝗲, I’m committed to delivering accurate, timely, and results-driven work that helps you meet your business goals. 💼 𝗪𝗵𝘆 𝗪𝗼𝗿𝗸 𝘄𝗶𝘁𝗵 𝗠𝗲? - 𝗘𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲: 𝟔𝟎𝟎+ 𝗷𝗼𝗯𝘀 and 𝟏𝟓𝗸+ 𝗵𝗼𝘂𝗿𝘀 with 𝗧𝗼𝗽 𝗥𝗮𝘁𝗲𝗱 𝗣𝗹𝘂𝘀 on Upwork. - 𝗔𝗰𝗰𝘂𝗿𝗮𝗰𝘆: 98%+ 𝘃𝗲𝗿𝗶𝗳𝗶𝗲𝗱 𝗲𝗺𝗮𝗶𝗹𝘀 (multi-tool validation + manual checks). - 𝗙𝗮𝘀𝘁 𝗧𝘂𝗿𝗻𝗮𝗿𝗼𝘂𝗻𝗱: I can generate 𝟭,𝟬𝟬𝟬+ 𝗹𝗲𝗮𝗱𝘀 𝗶𝗻 𝟮𝟰 𝗵𝗼𝘂𝗿𝘀 with my skilled team of 15+ members. - 𝗙𝗹𝗲𝘅𝗶𝗯𝗹𝗲 𝗣𝗿𝗶𝗰𝗶𝗻𝗴: Competitive rates from $𝟬.𝟮𝟬 𝘁𝗼 $𝟬.𝟱𝟬 𝗽𝗲𝗿 𝗿𝗼𝘄, customized to your project needs. 🔧 𝗧𝗼𝗼𝗹𝘀 𝗮𝗻𝗱 𝗘𝘅𝗽𝗲𝗿𝘁𝗶𝘀𝗲: I use the latest tools to ensure 𝘀𝗽𝗲𝗲𝗱 𝗮𝗻𝗱 𝗮𝗰𝗰𝘂𝗿𝗮𝗰𝘆 in every project: - LinkedIn Sales Navigator - Zoominfo, Crunchbase, Clearbit - RocketReach, Hunter io, UpLead - Google Advanced Search, Mailtester, Rapportive - Excel, Google Sheets, and more 🎯 𝐏𝐨𝐰𝐞𝐫𝐟𝐮𝐥 𝐄𝐦𝐚𝐢𝐥 𝐁𝐨𝐮𝐧𝐜𝐞 𝐕𝐞𝐫𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧 𝐓𝐨𝐨𝐥𝐬: - 𝗠𝗶𝗹𝗹𝗶𝗼𝗻𝗩𝗲𝗿𝗶𝗳𝗶𝗲𝗿 ➤ Bulk email verification & list cleaning to ensure minimal email bounce rates. - 𝗭𝗲𝗿𝗼𝗕𝗼𝘂𝗻𝗰𝗲 ➤ Comprehensive bulk email verification & list cleaning, designed to maintain high deliverability rates. - 𝗡𝗲𝘃𝗲𝗿𝗕𝗼𝘂𝗻𝗰𝗲 ➤ Industry-leading bulk email verification & list cleaning, guaranteeing accuracy and reliability for large lists. 📊 𝗦𝗲𝗿𝘃𝗶𝗰𝗲𝘀 𝗜 𝗢𝗳𝗳𝗲𝗿: - 𝗕𝟮𝗕 𝗟𝗲𝗮𝗱 𝗚𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝗼𝗻 - 𝗘𝗺𝗮𝗶𝗹 𝗟𝗶𝘀𝘁 𝗕𝘂𝗶𝗹𝗱𝗶𝗻𝗴 - 𝗖𝗼𝗻𝘁𝗮𝗰𝘁 𝗟𝗶𝘀𝘁 𝗕𝘂𝗶𝗹𝗱𝗶𝗻𝗴 - 𝗣𝗿𝗼𝘀𝗽𝗲𝗰𝘁 𝗟𝗶𝘀𝘁 𝗕𝘂𝗶𝗹𝗱𝗶𝗻𝗴 - 𝗟𝗶𝗻𝗸𝗲𝗱𝗜𝗻 𝗣𝗿𝗼𝘀𝗽𝗲𝗰𝘁𝗶𝗻𝗴 & 𝗢𝘂𝘁𝗿𝗲𝗮𝗰𝗵 - 𝗗𝗮𝘁𝗮 𝗦𝗰𝗿𝗮𝗽𝗶𝗻𝗴 & 𝗗𝗮𝘁𝗮 𝗘𝗻𝘁𝗿𝘆 - 𝗕𝗼𝗼𝗹𝗲𝗮𝗻 𝗦𝗲𝗮𝗿𝗰𝗵 - 𝗦𝗼𝗰𝗶𝗮𝗹 𝗠𝗲𝗱𝗶𝗮 𝗟𝗶𝗻𝗸𝘀 𝗗𝗶𝘀𝗰𝗼𝘃𝗲𝗿𝘆 (𝗟𝗶𝗻𝗸𝗲𝗱𝗜𝗻, 𝗧𝘄𝗶𝘁𝘁𝗲𝗿, 𝗙𝗮𝗰𝗲𝗯𝗼𝗼𝗸, 𝗜𝗻𝘀𝘁𝗮𝗴𝗿𝗮𝗺) 🚀 𝗥𝗲𝘀𝘂𝗹𝘁𝘀 𝗧𝗵𝗮𝘁 𝗠𝗮𝘁𝘁𝗲𝗿: Whether you need a targeted list for a cold email campaign or verified contact data to fuel your sales pipeline, I provide 𝟭𝟬𝟬% 𝗿𝗲𝗽𝗹𝗮𝗰𝗲𝗺𝗲𝗻𝘁 𝗳𝗼𝗿 𝗶𝗻𝘃𝗮𝗹𝗶𝗱 𝗹𝗲𝗮𝗱𝘀 and deliver results you can trust. 🌟 𝗖𝗹𝗶𝗲𝗻𝘁 𝗧𝗲𝘀𝘁𝗶𝗺𝗼𝗻𝗶𝗮𝗹𝘀: ⭐️⭐️⭐️⭐️⭐️ Jun 20, 2024 - Jun 30, 2024⏰ Tazmir exceeded expectations with phenomenal quality, delivered super fast, and communication was excellent. I'm so happy with the results and will definitely be using him again! ⭐️⭐️⭐️⭐️⭐️ May 9, 2023 - Jun 17, 2024⏰ Tazmir did a great job as a VA for us. We look forward to hiring him again as soon as we have more work for him. Thank you! ⭐️⭐️⭐️⭐️⭐️ Jun 8, 2022 - Feb 27, 2024⏰ Even though he is on the other side of the world for me, he was accessible like he was just next door! His communication and ability to see the big picture- is first rate. his work ethic is amazing on top of this he is a very nice man! ⭐️⭐️⭐️⭐️⭐️ Mar 30, 2021 - Nov 14, 2023⏰ Tazmir consistently delivers leads with outstanding accuracy and speed. He’s helped grow our outreach efforts by 20%! Highly recommended. Ready to grow your business? Let’s chat and see how I can help. Feel free to message me or invite me to discuss your project details.
- Data Cleaning
- Data Mining
- Data Entry
- Lead Generation
- List Building
- Online Research
- Data Scraping
- Email Marketing
- LinkedIn
- Data Science
- Google Sheets
- Prospect List
- B2B Lead Generation
- LinkedIn Lead Generation
- Contact List
Jakarta, Indonesia
Data Engineer specializing in Python ETL pipelines for cloud data warehouses. I build automated data engineering solutions processing millions of records daily. From real-time trading data to healthcare analytics 6+ years building production ETL systems on GCP and AWS using Apache Airflow, Dagster, and modern data stacks. I architect data engineering solutions that handle schema changes, ensure data quality, scale with demand, and prevent 3 AM pipeline emergencies. DATA ENGINEERING & ETL EXPERTISE ETL Pipeline Development & Data Engineering I design scalable ETL pipelines and data engineering infrastructure using Python with Apache Airflow or Dagster. My data engineering solutions include automated error handling, data validation, and comprehensive monitoring. Cloud Data Engineering (GCP & AWS) I build cloud-native data engineering solutions and ETL pipelines on modern platforms: • GCP: BigQuery, Dataflow, Cloud Functions, Pub/Sub • AWS: Redshift, Glue, Lambda, S3, Kinesis Enterprise data warehouse migration: Reduced ETL processing time 60% moving to GCP. Python Data Engineering & Pipeline Orchestration Python expert for data engineering and ETL development. I implement robust data workflow orchestration using Apache Airflow and Dagster with pipeline monitoring for data quality and reliability. KEY DATA ENGINEERING & ETL PROJECTS Election Data Pipeline - Python + Dagster data engineering solution extracting campaign finance data. Automated 40 hours/week of manual processing. Real-Time Trading Pipeline - Multi-layer data engineering architecture for algorithmic trading. Achieved <100ms latency, 100% uptime for streaming data. Healthcare Data Migration - Led enterprise ETL migration to GCP BigQuery. Result: 60% faster processing, 50% better performance. ML Feature Engineering - Built end-to-end data pipeline for AirAsia's recommendation system. Processed millions of records, increased engagement 25%. Web Scraping ETL - Automated data engineering solution combining scraping with warehousing using Python and Apache Airflow. DATA ENGINEERING TECH STACK ETL & Orchestration: Apache Airflow, Dagster, Apache Spark, Kafka, dbt Languages: Python (Expert), SQL (Expert) Cloud Platforms: GCP (BigQuery, Dataflow), AWS (Redshift, Glue, Lambda) Databases: PostgreSQL, MongoDB, BigQuery, Redshift, Snowflake Python Libraries: Pandas, PySpark, SQLAlchemy, Apache Beam Infrastructure: Terraform, Docker, Kubernetes, CI/CD. IDEAL PROJECTS • ETL pipeline development from scratch (Python, Airflow, cloud platforms) • Data warehouse engineering and cloud migration (BigQuery, Redshift, Snowflake) • Real-time data engineering and streaming ETL implementation • Legacy ETL modernization and data pipeline migration • Web scraping data engineering with ETL workflows • Data integration connecting multiple sources • ML data pipeline engineering for feature engineering LET'S BUILD YOUR DATA ENGINEERING SOLUTION Available for fixed-price data engineering projects and long-term ETL contracts. I work across US, European, and Asian time zones (GMT+7). Ready to discuss your data engineering and ETL needs? Send me a message. I respond within 2 hours during business hours.
- Data Engineering
- Python
- ETL Pipeline
- SQL
- dbt
- ClickHouse
- BigQuery
- Google Analytics
- Facebook Ads Manager
- MongoDB
- Apache Airflow
- Google Cloud Platform
- Amazon Web Services
Sonipat, India
Professional consultants with experience in Security, Data Analytics, Splunk, Cloud Ops, SIEM (Security Incident & Event Management), ITSM, etc.
- Data Engineering
- Security Analysis
- Data Analytics
- IT Consultation
- Splunk
- Solution Architecture Consultation
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
Laayoune, Morocco
Businesses generate data every day, but many still lack clear visibility into where leads, customers, and revenue actually come from. I help businesses analyze and optimize their business data pipeline by transforming scattered operational, sales, and marketing data into structured reporting systems and actionable insights. My goal is simple: help decision-makers better understand performance, identify bottlenecks, track KPIs, and improve business visibility. I can help with: • Business data analysis • KPI reporting & dashboarding • Sales and revenue analysis • Marketing performance tracking • Data cleaning & structuring • Automated business reporting I work with businesses that want reliable reporting, better operational visibility, and data-driven decision-making.
- Python
- LLM Prompt Engineering
- Data Analysis
- Campaign Reporting
- Business Intelligence
- Tableau
- SQL
- Microsoft SharePoint
- Knowledge Management
- Microsoft Power BI
- Analytics Dashboard
- Microsoft Excel
- Web Scraping
- Market Research
- Business Analysis
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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.
Find more freelancers
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