Hire Data Engineers | Vetted ETL & Pipeline Experts

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Hire data engineers through DOIT for ETL pipelines, data warehousing, real-time streaming, and cloud data platforms. DOIT handles sourcing, screening, contracts, and payroll, while the engineer joins your team ready to work.

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Why hire data engineers with DOIT

Vetted before you interview

DOIT evaluates every candidate through comprehensive technical assessments tailored to your project needs. Our vetting process examines real-world experience with data pipelines, distributed systems, big data frameworks, and cloud platforms to ensure only qualified data engineers reach your shortlist.

Cross-industry data experience

With successful placements across fintech, healthcare, e-commerce, logistics, defense tech, and SaaS sectors, DOIT connects you with data engineers who understand industry-specific data challenges and compliance requirements relevant to your business.

Talent across 12+ time zones

Hire remote data engineers who can work during your business hours with partial or complete overlap. DOIT's network spans over 12 time zones across the US, Canada, Poland, Ukraine, Romania, Bulgaria, Czechia, Argentina, Mexico, and Brazil.

Senior talent, less overhead

DOIT places only middle and senior data engineers from Europe, the US and LATAM and runs payroll, taxes, compliance, and equipment for them. You carry none of the admin overhead.

Scale your data team flexibly

Adjust your data engineering team size based on project phases and workload changes. Add specialists during intensive development periods or scale down after implementation with flexible contract arrangements.

Replacement guarantee

If the data engineer doesn't meet your expectations, DOIT sources a free replacement as soon as possible and runs a knowledge transfer. The guarantee covers the full engagement.

Meet top data engineers for hire

Top 1.5%

data engineers who pass DOIT vetting

$0 recruitment costs

pay only the rates of hired data specialists

2 weeks

typical time to start

Access DOIT’s pre-screened network of 654 data engineering experts across the US, Europe, and LATAM. Receive a tailored shortlist that matches your precise project needs and preferred time zone.

Carolina

Data Engineer

$50/hour

São Paulo, Brazil

Availability:

Part-time (25 hrs/week)

Tech stack: Python, SQL, Apache Airflow, Snowflake, AWS, Elasticsearch, Redis, Apache Hive, Docker, Kubernetes

A data engineer with 4 years of commercial experience in cloud data infrastructure and pipeline automation. Builds data lake architectures on AWS, with Apache Airflow orchestrating ingestion and transformation jobs. Implements warehouse models in Snowflake and caching layers with Redis and Elasticsearch. Has experience automating pipelines across containerized environments with Docker and Kubernetes.

Request CVs

Availability:

Part-time (25 hrs/week)

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Tomasz

Senior Data Engineer

$55/hour

Warsaw, Poland

Availability:

Full-time

Tech stack: Python, SQL, Apache Spark, Apache Kafka, Azure Data Factory, Databricks, PostgreSQL, MongoDB, Docker

A data engineer with 5 years of experience building production ETL pipelines and data warehouses. Builds batch and streaming pipelines in Apache Spark, with Apache Kafka moving events between systems. Implements warehouse and analytics layers in Databricks and Azure Data Factory. Has experience modeling data across PostgreSQL and MongoDB for analytics workloads.

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Availability:

Full-time

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Dmytro

Senior Data Engineer

$56/hour

Kyiv, Ukraine

Availability:

Full-time

Tech stack: Python, Scala, SQL, Apache Spark, Flink, Kafka, AWS, Google BigQuery, Airflow, Docker, Elasticsearch, Git

A skilled data engineer with 5 years of experience in distributed data processing and real-time analytics. Deep knowledge of the Apache Spark ecosystem and streaming technologies. Built data pipelines that handle terabyte-scale datasets with optimized performance.

Experienced in implementing data quality checks and monitoring systems. Strong background in both cloud and on-premise data infrastructure.

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Availability:

Full-time

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Andrés

Middle Data Engineer

$50/hour

Mexico City, Mexico

Availability:

Full-time

Tech stack: Python, SQL, Apache Spark, Apache Kafka, Azure SQL, Power BI, Apache Airflow, Docker, Flask

Experienced integration specialist with 3 years of commercial experience building analytics platforms from ingestion through reporting. Builds ETL pipelines in Apache Spark and Apache Airflow, with Azure SQL as the warehouse layer. Implements reporting datasets that feed Power BI dashboards. Has experience exposing data services through Flask APIs for product teams.

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Availability:

Full-time

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Marcus

Senior Data Engineer

$95/hour

Denver, CO, United States

Availability:

Full-time

Tech stack: Scala, Java, Python, Apache Spark, Apache Flink, Databricks, Google BigQuery, Apache Pulsar, Kubernetes, Terraform

Senior data engineer with 6 years of experience specializing in real-time data processing. Proficient in building streaming pipelines using Flink and Pulsar for high-throughput data ingestion. Implemented machine learning data pipelines and automated deployment processes with Kubernetes. Proven track record of mentoring junior engineers and establishing data engineering best practices.

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Availability:

Full-time

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Diego

Data Engineer

$53/hour

Buenos Aires, Argentina

Availability:

Full-time

Tech stack: Python, Scala, SQL, Apache Spark, Amazon Redshift, Apache Kafka, Redis, Docker, Jenkins, TensorFlow

ML-focused engineer with 4 years of experience building intelligent data processing systems. Builds pipelines in Apache Spark and Apache Kafka, with Amazon Redshift as the analytics warehouse. Implements feature pipelines that feed TensorFlow models, with Redis for low-latency lookups. Has experience automating deployments with Jenkins and Docker across Scala and Python services.

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Availability:

Full-time

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Raluca

Senior Data Engineer

$48/hour

Bucharest, Romania

Availability:

Part-time (30 hrs/week)

Tech stack: Python, Java, SQL, Apache Hadoop, Apache Hive, Cassandra, Elasticsearch, Azure DevOps, Kubernetes, Git

Senior data engineer with 7 years of commercial experience in big data processing and NoSQL database management. Builds large-scale batch pipelines in Apache Hadoop and Hive, with Cassandra handling distributed storage. Implements search and analytics layers in Elasticsearch.

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Availability:

Part-time (30 hrs/week)

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Discover 650+ data engineers for hire in the DOIT talent pool

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How to hire data engineers with DOIT Software

Share role details

Receive qualified profiles

Interview top candidates

Hire with confidence

Share role details

Connect with DOIT and outline your requirements for a data engineering role, including experience level, technology preferences, project scope, and time zone needs. The talent matching team will schedule a consultation to understand your goals and define the right candidate profile for your project.

Receive qualified profiles

DOIT analyzes the talent pool and presents data engineers who match your technical requirements and project needs. Each candidate undergoes a rigorous technical assessment and soft skills evaluation before their profile reaches you.

Interview top candidates

Choose which data engineers to interview and conduct as many rounds as needed. DOIT coordinates scheduling and can arrange additional technical assessments tailored to your specific requirements upon request.

Hire with confidence

Once you select your ideal data engineer for hire, DOIT manages all administrative aspects, including contracts, equipment provisioning for remote team members, and ongoing HR support. Our team remains available throughout the engagement for feedback and assistance.

What data engineers from DOIT can build for you

ETL and ELT pipelines

Create automated workflows that ingest, transform, and load data from multiple sources into your data warehouse or lake.

Hire data engineers to design pipeline architectures using Apache Airflow or Azure Data Factory, implement data quality checks, and establish monitoring for reliable data processing.

Data warehouse and lakehouse modeling

Hire data warehouse engineers who model the warehouse your analytics run on.

They structure dimensional models in Snowflake, BigQuery, Redshift, or Databricks, and add lakehouse table formats when data volume requires it.

Real-time and streaming

Hire big data engineers for real-time and streaming workloads.

They build low-latency systems in Apache Spark and Flink, with Kafka moving events as they arrive so dashboards and alerts stay current.

Data integration

Hire data integration engineers to connect the systems across your business.

They pull data from CRMs, product databases, third-party APIs, and event streams into one place your team can query.

Data migration

Hire data migration engineers for warehouse moves and platform upgrades.

They keep records intact and downtime low across on-prem to cloud and warehouse-to-warehouse upgrades.

Data management and automation

Hire data management engineers to keep pipelines running reliably and data accurate after launch.

They automate recurring workflows, add data-quality checks at each stage, tune database performance, and document the pipeline.

Want to hire the right data engineer for your project?

Let's discuss your data infrastructure needs, and DOIT will help you hire data engineers with relevant experience for your tasks.

Hire data engineers with relevant tech skills

DOIT data engineers work with modern technology stacks across different categories to build robust data infrastructure and processing systems.

Languages

Python

SQL

Scala

Java

Big Data frameworks

Spark

Kafka

Flink

Airflow

Pulsar

dbt

Cloud platforms & data services

Microsoft Azure

AWS

GCP

Databricks

Snowflake

Apache Iceberg

Delta Lake

Databases & data storage

PostgreSQL

MySQL

MongoDB

Redis

ElasticSearch

DevOps & Infrastructure

Kubernetes

Jenkins

Azure DevOps

Terraform

Business intelligence tools

Power BI

Tableau

How DOIT vets data engineers

Experience review

DOIT checks the engineer's commercial history with pipelines, warehouses, streaming systems, and the cloud platforms they have shipped on. In the live interview, DOIT goes through SQL and data modeling, then the design choices behind the engineer's past pipelines and how they handled scale and failure in production.

Pass rate: 14.3%

Hands-on technical test

DOIT can set a practical task built around your stack, such as designing a pipeline or optimizing a slow query against a realistic dataset. DOIT reviews the result for correctness and efficiency, and for how the engineer reasons through trade-offs, so you see proof of skill before you book an interview.

Pass rate: 5%

Fit confirmation

DOIT evaluates how candidates match your collaboration needs, from time zone preferences to work style compatibility. For roles requiring real-time coordination, we source engineers who can maintain substantial overlap with your business hours. We also assess adaptability to remote work environments and readiness for dynamic project requirements.

Pass rate: 1.5%

Let's accelerate your data infrastructure development!

Hire experienced data engineers who can transform your data processing capabilities.

Talk to hiring experts

FAQs about hiring data engineers

How much does it cost to hire a data engineer?

The cost of hiring a data engineer varies based on location, experience level, project complexity, and engagement type. According to Glassdoor, annual salaries for data engineers in the US range from $102K to $168K per year. Hourly rates typically range from $70 to $150+ in North America and from $45 to $75+ in Eastern Europe and Latin America. With DOIT, you pay only the specialist's rate with no additional recruitment fees or overhead costs.

How long does it take to hire a data engineer with DOIT?

OIT sends the first CVs within five business days for a standard data engineering role. A more specialized brief, like a streaming or lakehouse expert on a particular cloud, can take a few days longer to match. Our hiring team will provide clear expectations and regular updates throughout the process.

What engagement models are available for hiring data engineers?

DOIT specializes in staff augmentation services, providing data engineers who integrate into your existing development teams for full-time or part-time engagement. Through collaboration, you maintain full control over daily management while DOIT handles all administrative, legal, and HR responsibilities for the specialists. DOIT also offers recruitment services for organizations seeking to hire data engineers directly as permanent employees.

What's the difference between a data engineer vs data scientist?

A data engineer builds and maintains the pipelines and infrastructure that move and store your data. A data scientist works on top of that foundation, using the data to build models and predictions. If your reports are slow or your team cannot get clean data to work with, the bottleneck is engineering, and a data engineer is the role to hire first.

What skills should I look for in a data engineer?

Look for strong SQL and data modeling first, since most data engineering work runs through them. On top of that, look for hands-on pipeline experience in a framework like Spark or Kafka, comfort with at least one cloud platform, and transformation work in dbt. For senior roles, the signal is usually in how the engineer handles scale and reliability: partitioning, retries, data-quality checks, and recovering a pipeline after a bad load. Python or Scala covers the scripting most production teams need.

What if the hired data engineer doesn't meet expectations?

DOIT offers a talent guarantee with free replacement services if a data engineer doesn't align with your needs. We facilitate knowledge transfer to ensure project continuity during any transition. Our thorough vetting process minimizes this risk, but we remain committed to finding the right match for your team.

What types of data engineers does DOIT provide?

DOIT places data engineers across pipeline and ETL work, warehouse and lakehouse modeling, real-time streaming, integration, and migration. Some specialize in one area, and senior engineers often cover several. You can hire one engineer for a focused role, or have DOIT assemble a small data team that covers the whole pipeline.

Where are DOIT's data engineers located?

DOIT places data engineers across the US, Canada, Poland, Ukraine, Romania, Bulgaria, Czechia, Argentina, Mexico, and Brazil. Most work remotely and overlap with North American and European business hours.

Hire Data Engineers Who Build Reliable Data Pipelines

Why hire data engineers with DOIT

Meet top data engineers for hire

Carolina

Tomasz

Dmytro

Andrés

Marcus

Diego

Raluca

How to hire data engineers with DOIT Software

Share role details

Receive qualified profiles

Interview top candidates

Hire with confidence

What data engineers from DOIT can build for you

ETL and ELT pipelines

Data warehouse and lakehouse modeling

Real-time and streaming

Data integration

Data migration

Data management and automation

Hire data engineers with relevant tech skills

How DOIT vets data engineers

Experience review

Hands-on technical test

Fit confirmation

FAQs about hiring data engineers

How much does it cost to hire a data engineer?

How long does it take to hire a data engineer with DOIT?

What engagement models are available for hiring data engineers?

What's the difference between a data engineer vs data scientist?

What skills should I look for in a data engineer?

What if the hired data engineer doesn't meet expectations?

What types of data engineers does DOIT provide?

Where are DOIT's data engineers located?

How much does it cost to hire a data engineer?

What skills should I look for in a data engineer?

How long does it take to hire a data engineer with DOIT?

What if the hired data engineer doesn't meet expectations?

What engagement models are available for hiring data engineers?

What types of data engineers does DOIT provide?

What's the difference between a data engineer vs data scientist?

Where are DOIT's data engineers located?

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