Hire The Best Data Engineers, Anywhere With Teamified
Find skilled professionals ready to drive results - hired in days, not weeks.
At Teamified, we connect you with world-class talent across a wide range of industries and business functions. Our streamlined process guarantees you get leading data engineering professionals - fast and hassle-free - so you can scale without the headaches.
The smarter way to build your data engineering team.
Struggling to turn fragmented data into valuable insights? Our data engineers work with platforms like Snowflake, Azure, and AWS to design pipelines that centralise, clean, and optimise your data for business intelligence. Teamified talent, 100% dedicated to your business, driving growth and delivering results.
Why Choose Teamified
We make hiring data engineers simple, fast, and reliable
Speed
Hire in days with our pre-vetted talent pool
Quality
Top 3% of data engineers with proven track records
Compliance
All candidates verified for certifications and background
Cost-Efficiency
Save up to 70% compared to traditional hiring
Ongoing Support
Dedicated account manager and replacement guarantee
Our Streamlined Hiring Process
From requisition to onboarding in 7 simple steps
Submit Requirements
Post your hiring requisition in 2 minutes
AI-Powered Matching
Instantly matched with our thousand-talent pool
Review Profiles
Access comprehensive candidate data and portfolios
Watch AI Interviews
View pre-recorded AI interviews of matched talent
Recruiter Screening
Optional initial interview or schedule directly
Extend Offer
Make your offer with confidence
Onboarding & Support
We handle onboarding, management, and ongoing support
Submit Requirements
Post your hiring requisition in 2 minutes
AI-Powered Matching
Instantly matched with our thousand-talent pool
Review Profiles
Access comprehensive candidate data and portfolios
Watch AI Interviews
View pre-recorded AI interviews of matched talent
Recruiter Screening
Optional initial interview or schedule directly
Extend Offer
Make your offer with confidence
Onboarding & Support
We handle onboarding, management, and ongoing support
How experienced are our data engineers?
From emerging talent to seasoned experts, we have the right fit for your needs
1-3 years exp.
- Basic understanding of data modelling, ETL concepts, and SQL queries
- Experience assisting with data extraction, transformation, and loading tasks
- Familiarity with cloud data platforms like Snowflake, Azure Data Lake, or AWS Redshift
- Knowledge of scripting languages such as Python or SQL for automation
- Exposure to data warehousing and basic reporting solutions
- Ability to work with large datasets and perform basic data validation
3-5 years exp.
- Strong experience building and optimising ETL pipelines and data warehouses
- Proficiency with cloud services (Snowflake, Azure Synapse, AWS Glue)
- Ability to develop and maintain scalable data architectures
- Experience implementing data quality, governance, and security measures
- Knowledge of orchestration tools like Airflow, Data Factory, or Step Functions
- Ability to collaborate with data analysts, scientists, and business stakeholders
5-7 years exp.
- Expert in architecting complex, large-scale data solutions in cloud environments
- Advanced skills in performance tuning, real-time data streaming, and data lakes
- Experience leading data migration, modernisation, and big data projects
- Strong mentorship abilities, guiding junior data engineers and analysts
- Ability to advise on best practices in data architecture, governance, and compliance
- Deep understanding of industry-specific data regulations and standards
What to check when hiring data engineers
Data Engineers build the infrastructure that makes analysis possible — pipelines, warehouses, transformation layers, and the data models that everything downstream depends on. Bad data engineering creates silent errors that corrupt reporting for months before anyone notices. Hire for production discipline, scalability thinking, and the kind of documentation habits that let the next engineer understand what was built.
Production pipeline experience
Ask for a pipeline they've built that is currently running in production — what it ingests, how it transforms, where it lands, and how they monitor it. Candidates who've only built proof-of-concept pipelines lack the production reliability mindset the role requires.
Data modelling depth
Ask them to describe the data model they'd build for a common use case — e.g., a customer purchase history mart for marketing analytics. Dimensional modelling (star schema, slowly changing dimensions) is foundational. Candidates who don't know these concepts build unscalable structures.
Platform-specific depth
Snowflake, Azure Synapse, and AWS Redshift each have distinct architectural patterns and cost levers. Ask for hands-on examples in the platform you're using — not just general cloud data experience.
Data quality and observability
How do they know a pipeline is producing correct output? Ask about their approach to data quality testing (dbt tests, Great Expectations, custom validation) and alerting when pipelines fail or data drift occurs.
Must-have skills
🚩 Red flags to watch for
All pipeline experience is proof-of-concept — nothing in production
Cannot explain a star schema or slowly changing dimension
Cloud data warehouse experience is purely query-based — no pipeline or model development
No data quality testing or monitoring in their pipelines
Pipelines are undocumented — 'it's in my head'
No version control for pipeline code
dbt proficiency is the clearest signal of modern data engineering maturity
Candidates who use dbt in production pipelines have almost universally adopted version control, automated testing, and documentation as standard practice. The tool enforces good habits in ways that raw SQL scripts or notebook-based pipelines do not. If you're building a modern data stack, dbt experience is one of the most reliable indicators of the engineering rigour you need.
Interview questions
"Describe a data pipeline you've built that runs in production. What does it ingest, how is it transformed, and how do you know it's working?"
Production pipeline ownership is the core signal — this tests real depth vs. theoretical knowledge.
"How would you model customer order data in Snowflake for a marketing analytics use case?"
Data modelling decisions determine downstream query performance and analysis flexibility.
"A pipeline that ran successfully yesterday is now producing zero rows. Walk me through how you'd diagnose it."
Debugging production pipelines is the most common daily reality — this tests systematic problem-solving.
"How do you implement data quality checks in your pipelines, and what happens when they fail?"
Data quality failure modes are often silent — this tests whether they've built safety nets.
Ways to hire a data engineers
Every model has trade-offs. Here's how they compare so you can choose the right fit for your team.
General options
Local full-time
Hire directly in your city. Full cultural alignment and in-office presence, but the talent pool is limited and salaries are high.
Freelancer
Engage on a task or sprint basis. Fast to start, but loyalty is low and availability is never guaranteed long-term.
Dev agency
Hand off a scoped project to an agency. Good for defined deliverables, but you pay a premium and own very little of the relationship.
Via Teamified
Offshore staffing
Get a dedicated, full-time data engineers — vetted, onboarded, and HR-managed by Teamified. Same output as a local hire, at a fraction of the cost.
On salary costs vs. hiring locally
- Hire in as little as 7 days
- Full-time, dedicated to your team
- We handle HR, payroll & compliance
- Replacement guaranteed
- No lock-in contract after minimum term
Executive search
We headhunt the talent that isn't actively looking. Deep network access, thorough vetting, and a curated shortlist — you make the final call.
Industry average is 15% — you keep the difference
- Access passive, hard-to-find talent
- Shortlist of pre-vetted candidates
- Confidential & discreet process
- Replacement guaranteed
- No lock-in contract
Managed recruitment
Hand us the brief and we run the whole process — sourcing, screening, interviews, and offer management. Your team stays focused on the business.
Up to 3 roles · 3-month minimum
- Job brief to offer in weeks, not months
- Screened, interviewed & reference-checked
- We manage candidate communications
- Replacement guaranteed
- No lock-in contract
What Our Clients Say
Trusted by companies worldwide
The flexibility and cultural fit made a huge difference. It wasn't just about filling seats - it was about finding the right people.
Nick Maait
Head of Engineering, Butn
Have a chat with Teamified. You will get a sense that it's much more of a relationship situation where they're really wanting to understand your business, as opposed to a more transactional experience, which is what we found talking with some other providers. The good thing is, there's a team behind you if you pick the right partner to help.
Ryan Ebert
Founder and CEO, Innings
Using Teamified is so much easier. One fee—then they handle all the HR stuff, so you have one less headache as you grow your business. All you want to do is minimise your headaches, and that's what Teamified does.
Ash Brown
Founder and CEO, Empiraa
I encourage all founders to treat this no different than hiring a local resource. The best thing about Teamified? They find great talent, vet them, and give you the flexibility to be as involved as you want in the hiring process.
Michael Nuciforo
Co-Founder and CEO, Thriday
Why our employees love working with Teamified
Keen to know more about our culture?
My favourite part would be the opportunity for growth. I've seen it in the short time that I've been here, and I'm looking forward to more.
JC,
Account Manager
We build culture like we build teams, intentionally
We're proud to have a 4.4 Glassdoor rating that backs that up. Because when people love showing up, great things happen.
Explore Related Roles
Find the perfect fit for your team
Data Analysts
Transform data into actionable business insights
Data Scientists
Build predictive models and advanced analytics solutions
Database Administrators
Manage and optimize database systems and performance
Cloud Architects
Design scalable cloud infrastructure solutions
Business Intelligence Analysts
Create dashboards and reports for business decision-making
DevOps Engineer
Streamline deployment and infrastructure management
Find the right hire, faster.
Talk to our team and get expert advice on the best hiring model for your business.
No obligations. No hard sell.