Data pipelines
Build and maintain the pipelines that move data from your product, tools and partners into one reliable place.
Hire senior data engineers, embedded in your team
Data engineers from Latin America who build the pipelines and data layers your product runs on. They work your hours, join your standups and stay. 40–60% below US rates.
Book a call
A short call about your roadmap and the roles you need.
Senior data engineer
Typical profile, matched to your stack
- Python
- SQL
- Spark
- Airflow
- Works in your timezone
- Joins your team, not a ticket queue
- 40–60% below US rates
40–60%
below US rates, at senior level
3,500+
ready, pre-vetted profiles
2–4 weeks
from first call to a productive team
Companies that trusted us
See their projectsWhat they own
What a senior data engineer owns
Data work breaks quietly. Pipelines drift, numbers stop matching and the AI roadmap stalls on data that isn't ready. A senior data engineer owns that layer, so your product, analytics and ML teams can build on it.
Data models and storage
Design schemas and data layers that stay fast and understandable as your volume grows.
Data quality
Add checks, tests and monitoring so your teams can trust the numbers they report on.
Analytics enablement
Give product, finance and leadership teams clean, documented data for analytics and BI.
AI/ML readiness
Prepare the datasets and feature pipelines your AI and ML work depends on.
Cloud data infrastructure
Run data workloads on AWS or GCP with your platform team, with cost and reliability in mind.
Skills and stack
Data engineering skills and stack
Languages
Processing & orchestration
Warehouses & databases
Cloud & tooling
How we vet
How we vet senior engineers
Strict technical and attitudinal filters, so the engineers you meet are already aligned with your role, your stack and your team.
- 01
Technical depth
We assess the seniority your role needs: how they design, decide and own work.
- 02
Attitude and team fit
We filter for how people communicate, collaborate and own their work inside a team.
- 03
Aligned with your role
Only candidates who match what you need reach you, so your time goes to real options.
3,500+
ready, pre-vetted profiles
Three ways to hire a senior data engineer
Staff Augmentation
Add one or more data engineers to your team, working under your data or platform leads.
Explore Staff AugmentationDedicated Team
Build a data pod with engineers, QA and a PM around one data product or platform.
Explore Dedicated TeamsEnd-to-End Delivery
Hand us a data initiative, such as a new pipeline or analytics layer, and we deliver it.
Explore End-to-End DeliveryFAQ
Hiring data engineers with us
What stack do your data engineers work with?
Digital Beings' data engineers work with Python, SQL, Scala and Java; Spark, Kafka and Airflow; and warehouses such as Snowflake, BigQuery, Redshift and Databricks, on AWS, GCP or Azure. Tell Digital Beings your stack, and it matches engineers who know it.
Can a data engineer join our existing data or platform team?
Yes. A Digital Beings data engineer joins your standups, uses your tools and works under your leads, like any member of your team.
Do you also hire AI/ML engineers?
Yes. Digital Beings staffs both roles. Data and AI/ML work often go together, so you can add either as individual engineers or as one team.
How fast can a data engineer start?
A productive data engineer can be on your team in 2–4 weeks. Digital Beings draws from 3,500+ ready, pre-vetted profiles, so you skip the months-long search. You interview the shortlist, and on a call Digital Beings confirms the plan for your role.
What does a senior data engineer cost?
Digital Beings' rates for a senior data engineer are 40–60% below US rates. The exact rate depends on seniority and stack, and Digital Beings walks you through it on a call.
