Hire the Top 1.3% of Data Engineers

Turn Raw Data into Business Insights: Optimize Operations and Enhance Decision-Making with Skilled Data Engineering
Typescouts pairs you with global talent specific to your needs —fast, affordable, and perfectly matched to your company’s culture.
“Typescouts somehow always finds us the best people for our team.”
Andrea H, COO

Unlock huge savings by hiring a pre-vetted, remote Data Engineer

Hiring in the us

$130,000

Annually
USA
Hiring with typescouts

$42,000

Annually
67% less
Typescouts

Hire your Data Engineer for up to 67% less

Talent matched to your exact needs within 4-10 days
Fully vetted and interviewed candidates
Candidates have great English, western culture experience, and work in your timezone
Backed by our 90 Day Happy Hire Guarantee

Hire Data Engineers

Vetted for

Tech & Soft Skills

Verified for

Remote Performance

Something else

Curated Performance

Rafael K.
Mexico
Hire
Rafael K.
Data Pipeline Specialist
I’m a data pipeline specialist with 4 years of experience designing scalable data architectures. Skilled in Python, SQL, and AWS, I’ve led projects optimizing ETL processes, reducing query time by 60% for a major e-commerce client. Passionate about automation and data reliability.
Luciana R.
Brazil
Hire
Luciana R.
Big Data Engineer
With 6 years in big data engineering, I specialize in data architectures using Spark and BigQuery. I’ve automated pipelines that saved 300+ hours yearly for my team. Experienced in data warehousing and Google Cloud, I thrive on creating efficient, scalable solutions.
Ignacio O.
Peru
Hire
Ignacio O.
Senior Data Engineer
Senior data engineer with 6+ years in SQL, Hadoop, and ETL. I architected a data warehouse that improved data accessibility by 40%. Proficient in Python and Kafka, I’m passionate about building scalable systems that support impactful analytics and insights.
Carmela N.
Philippines
Hire
Carmela N.
Data Infrastructure Engineer
I have 3 years of data engineering experience, specializing in Azure, SQL, and Spark. I built a data pipeline that improved processing speeds by 50% for a financial services client. Known for my attention to detail, I ensure high-quality, reliable data solutions.
Matías H.
Argentina
Hire
Matías H.
Cloud Data Engineer
I've been a cloud data engineer with 5 years of experience in SQL, Python, and AWS. I developed a system that reduced data processing time by 45% for a SaaS company. I'm skilled in ETL and cloud technologies and I’m dedicated to data efficiency and ensuring fast, actionable insights.
Aleah R.
Philippines
Hire
Aleah R.
ETL Developer
I bring 6 years of experience in data engineering with expertise in Google Cloud, Python, and Airflow. I implemented an ETL process that saved $50k annually in data costs. I'm skilled at creating streamlined, reliable data flows to support high-quality business analytics.
Let us find you the perfect match.
Start hiring
Vetted for

Tech & Soft Skills

Verified for

Remote Performance

Seamless

Team Integration

“Outstanding service! The team at Typescouts goes above and beyond to find precisely the right talent for your needs.  Highly recommend their services for anyone seeking exceptional talent."
- Maxim T., Business Owner
experience Levels

Choose the right fit for your needs

Junior Level Indicator

Junior Data Engineer

Ideal for startups and small businesses needing foundational data support or simpler data pipelines.
Experience

1 - 2 years

Skillset
  • Experience: 1-2 years in data engineering, typically with experience in supporting ETL processes and database management.
  • Skills: Basic SQL, Python, and experience with one cloud platform like AWS or Google Cloud.
  • Results: Can establish basic data pipelines, ensuring data is organized and accessible for reporting and analysis.
  • Mid Level Indicator

    Mid-Level Data Engineer

    Ideal for growing companies needing streamlined data processes and more robust data infrastructure.
    Experience

    3 - 5 years

    Skillset
  • Experience: 3-5 years in data engineering, with experience in building scalable ETL systems and managing data warehouses.
  • Skills: Proficient in SQL, Python, and multiple cloud platforms, with experience in tools like Apache Spark and Airflow.
  • Results: Able to optimize data processing, improving data accessibility, quality, and processing time to support efficient decision-making.
  • Senior Level Indicator

    Senior Data Engineer

    Ideal for enterprises with large-scale data needs, complex data environments, or real-time data requirements.
    Experience

    5+ years

    Skillset
  • Experience: 6+ years, often leading data infrastructure projects and handling high-volume data processing.
  • Skills: Advanced proficiency in SQL, Python, multiple cloud services, and big data tools like Hadoop and Kafka.
  • Results: Can design and oversee complex data architectures, enabling predictive analytics and real-time insights, and ensuring data reliability across the organization.
  • Hiring for a Data Engineer? Explore practical use cases

    Customer Behavior Analysis

    Data engineers can create systems that track customer interactions across various platforms. This helps businesses understand purchasing patterns, preferences, and trends, enabling tailored marketing strategies and improved customer experiences.

    Data Integration

    By integrating data from multiple sources—such as sales, marketing, and customer service—data engineers ensure all relevant information is accessible in one place. This holistic view supports better decision-making and helps identify growth opportunities.

    Real-Time Analytics

    Data engineers can set up real-time data processing systems that provide immediate insights. For example, businesses can monitor sales data as it happens, allowing for quick adjustments to marketing campaigns or inventory levels to maximize sales.

    Predictive Analytics

    With the right data infrastructure, data engineers can enable predictive analytics. This allows companies to anticipate future trends and behaviors, like predicting which products will be in high demand, helping to optimize inventory and reduce waste.

    Data Quality Management

    Data engineers implement processes to clean and validate data. This ensures that the data used for analysis is accurate and reliable, leading to better-informed decisions and reducing the risks associated with poor-quality data.

    Enhanced Reporting

    By automating data collection and reporting processes, data engineers free up time for teams to focus on analysis rather than data gathering. This enhances the quality and speed of reports, providing stakeholders with timely insights for strategic planning.
    Our Approach

    Your new Data Engineer is a week away, all in 3 simple steps

    Uncomplicated and stress-free. Hiring made easy, satisfaction guaranteed.

    1

    Tell us what you need, and we'll begin the search.

    Book a free call with us. Our team will meet with you to get the details on the role you're looking for, and answer any questions you might have.

    2

    We present you with screened, ready-to-hire candidates.

    We'll begin our talent search for your role. We'll interview candidates until we are ready to present a group of hand picked candidates that are well suited for your needs. On average, this takes 4-10 days.

    3

    If you love your pick, we'll help place them on your team.

    We'll present you with handpicked candidates for you to consider, and interview if you'd like. After selecting the ideal pick, you'll pay a one-time flat fee; no hidden charges. Anyone you hire is backed by our 90 Day Happy Hire Guarantee. We're not happy until you are.
    “I've made several hires and the experience is simply amazing. My new staff is now a core part of our team. Will be back for more!”
    - Derek J, founder
    Uber logoCrate&Barrel LogoUnilever logoDoordash Logo

    FAQs

    What exactly does a data engineer do, and why is their role critical?

    A data engineer is responsible for creating, managing, and optimizing data pipelines that transform raw data into useful information. Their role is crucial because they ensure data is accessible, reliable, and efficiently organized, which enables data scientists and analysts to make data-driven decisions. Data engineers build the infrastructure, handle big data, and work with complex systems, ensuring data is consistently available and accurate for analysis, machine learning, and business intelligence.

    When should my startup consider hiring a data engineer?

    A data engineer is needed when your business relies heavily on data for decision-making, you need a more organized data pipeline, or your data complexity has outgrown existing solutions. For early-stage startups, hiring might be necessary if data management tasks consume too much of your team’s time or if you need to scale data operations quickly.

    What skills should I look for when hiring a data engineer?

    Key skills for data engineers include:

    • Programming languages: Python, Java, and Scala are common.
    • Database management: SQL, NoSQL, and cloud-based databases (e.g., AWS Redshift, Google BigQuery).
    • ETL (Extract, Transform, Load): Experience with tools like Apache Airflow, Talend, or Informatica.
    • Big Data technologies: Proficiency with Hadoop, Spark, and Kafka.
    • Data warehousing: Knowledge of designing and maintaining data warehouses.
    • Cloud experience: Familiarity with AWS, Azure, or Google Cloud.
    • Problem-solving abilities: Data engineering involves overcoming challenges like scaling systems and optimizing storage.

    How do data engineers differ from data scientists and analysts?

    Data engineers focus on building and maintaining the infrastructure for data generation, storage, and accessibility. Data scientists use this data to create predictive models and derive insights, while data analysts interpret data and generate reports. Data engineers ensure the data is high-quality, while scientists and analysts make sense of it.

    How much does it cost to hire a data engineer?
  • USA: Data engineers in the U.S. typically command an annual salary between $100,000 and $150,000, depending on experience and location.
  • Latin America: In LATAM countries, you can expect to pay between $30,000 and $550,000 per year for skilled data engineers. This range can vary based on the country and level of expertise.
  • Philippines: Hiring from the Philippines is even more cost-effective, with annual salaries ranging from $25,000 to $40,000 for qualified data engineers. This is ideal for budget-conscious startups without compromising skill quality.
  • How do I assess a data engineer’s technical expertise during the interview?

    Assessing technical expertise involves asking candidates to discuss past projects, provide code samples, and solve problems relevant to your data needs. Use coding challenges or practical tests to evaluate their proficiency in SQL, ETL processes, or big data tools like Spark. Asking them to walk through how they’d approach a real-world problem can reveal problem-solving skills.

    What challenges can I expect when onboarding a new data engineer?

    Onboarding challenges include familiarizing the engineer with your company’s data architecture, tools, and business processes. To ease the process, provide detailed documentation, a mentor for initial guidance, and clear expectations. Regular check-ins during the onboarding period can help address any questions and accelerate integration into the team.

    What kind of projects can a data engineer handle?

    Data engineers are involved in:

    • Building and maintaining data pipelines to support continuous data flow.
    • Integrating diverse data sources from applications, sensors, or external sources.
    • Developing and managing ETL processes to clean and structure data.
    • Optimizing databases and storage systems for performance and scalability.
    • Setting up data warehousing solutions for analysis and reporting.
    • Implementing security protocols to protect data.

    What questions should I ask during a data engineer interview?

    Some questions you can ask are:

  • “Describe a data pipeline you built and the challenges you faced.”
  • “How do you ensure data quality and consistency across different sources?”
  • “What’s your approach to scaling a data system as the business grows?”
  • “How have you handled data security and privacy in your previous roles?”
  • Why should I hire a data engineer from Typescouts?

    Typescouts specializes in connecting you with top-tier data engineering talent, offering:

    • Speed: Swift, efficient recruitment that matches your timeline.
    • Quality: Access to highly-vetted data engineers skilled in the latest technologies.
    • 90-Day Happy Hire Guarantee: If you’re not satisfied within the first 90 days, we’ll help you find a replacement at no additional cost.

    Ready to work together?

    We'll find you amazing employees for up to 80% less.
    Start Hiring
    Tim Sherstyuk
    Founder