Hire remote
Big Data Engineer
Build scalable, high-performance data pipelines with expert big data engineers skilled in Hadoop, Spark, Kafka, and AWS architectures.
Why now
Why US startups hire remote
Lower costs:
Save 50–70% compared to local salaries.
Access to global skills:
Tap into a vetted network of hire remote QA engineer talent across the Philippines, Latin America, and South Africa
Time zone alignment:
Get full workday overlap with U.S. hours.
Scalable and flexible:
Add or remove QA engineers as your testing needs evolve. With Hire Overseas, you don’t just fill roles — you build a world-class, distributed QA and testing team.
Why us
Why hire through Hire Overseas
Rigorous Vetting
Every engineer passes a 3-stage assessment covering distributed data systems, ETL pipelines, cloud platforms, and communication.
Global Talent Network
We source from the top 3 talent regions — the Asia, Latin America, and South Africa — ensuring technical excellence and cultural alignment.
Fast Matching
Tell us what you need, and we’ll match you with pre-vetted big data engineers within 48 hours.
Guaranteed Quality
Start risk-free. If you’re not satisfied, we’ll replace your hire — free of charge.
The process
How it works
Tell us your requirements
Share your data architecture, platforms, volume, and pipeline needs.
Get matched in 48 hours
We send pre-screened big data engineers with proven large-scale experience.
Interview & hire
You choose the engineer who fits your your data stack and project goals.
Onboard & start building
Your new engineer begins working — aligned with your U.S. time zone.
Questions
Hiring for this role.
They design ETL pipelines, build distributed systems, integrate data sources, optimize clusters, manage cloud pipelines, and support advanced analytics.
Yes — we provide experts in Hadoop ecosystems, Spark streaming, Kafka processing, Airflow orchestration, and large-scale data pipelines.
Absolutely. Our talent includes AWS, Azure, and GCP-certified data engineers experienced in Redshift, BigQuery, EMR, Glue, and more.
You’ll receive a shortlist within 48 hours and typically hire within 10–14 days.
Most companies save 50–70% while gaining access to elite distributed data engineering talent.
