Elite Data Engineers. Ready to Plug In. Anywhere.

Work with data engineers who’ve built high-throughput pipelines, real-time ML infrastructure, and governed platforms at scale.

Available globally — US In-Office | US Remote | Global Remote
Get 2 Reference CVs
Hire a Data Engineer
At a global pharma major, we deployed AI-driven validation layers to ensure data integrity and GxP compliance in clinical trials.
At a $100B engineering firm, we restructured pipeline architecture to enable self-serve analytics across 12 BUs. And for a healthtech startup, we built reusable data layers that cut dashboard dev time by 70%.

What We Offer

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Our data engineers are execution-ready and elite - trained to ship, not just spec.
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End-to-End Pipeline Development
Design and deploy robust ETL/ELT flows across real-time and batch systems — built for volume, speed, and data fidelity.
Data Architecture & Modeling
Refactor legacy data models or build from scratch — optimizing for scale, discoverability, and cross-use in BI, ML, and GenAI.
Cloud & On-Prem Integration
Build resilient data layers across AWS, Azure, GCP, or hybrid environments — with deep tooling and security alignment.
Real-Time & Event-Driven Processing
Implement Kafka, Spark, or Kinesis-based architectures to enable real-time analytics and AI model retraining.
Governance, Lineage & Quality Enforcement
Automate schema validation, lineage capture, and drift detection — with built-in auditability and role-based access.
ML & GenAI-Ready Infrastructure
Power feature stores, embedding pipelines, and retrieval-augmented generation with structured, traceable data flow.

End-to-End Pipeline Development

Design and deploy robust ETL/ELT flows across real-time and batch systems — built for volume, speed, and data fidelity.

Data Architecture & Modeling

Refactor legacy data models or build from scratch — optimizing for scale, discoverability, and cross-use in BI, ML, and GenAI.

Cloud & On-Prem Integration

Build resilient data layers across AWS, Azure, GCP, or hybrid environments — with deep tooling and security alignment.

Real-Time & Event-Driven Processing

Implement Kafka, Spark, or Kinesis-based architectures to enable real-time analytics and AI model retraining.

Governance, Lineage & Quality Enforcement

Automate schema validation, lineage capture, and drift detection — with built-in auditability and role-based access.

ML & GenAI-Ready Infrastructure

Power feature stores, embedding pipelines, and retrieval-augmented generation with structured, traceable data flow.

Why Ideas2IT

Top-Tier Talent, Vetted by Delivery Track Record

Our engineers don’t just tick boxes — they’ve shipped critical systems across regulated industries, fast-moving startups, and multi-cloud enterprise stacks.

Cross-Tool, Cloud-Native, Infra-Aware

They’re fluent in dbt, Spark, Kafka, Airflow, Snowflake, BigQuery, Redshift, Terraform, Looker, and more.

Plug-In Speed. No Ramp-Up Drag.

Whether embedded in your team or deployed as a pod, our engineers start delivering from Week 1 — no hand-holding, no waiting.

Compliance-Aware by Default

Whether HIPAA, SOC 2, or GxP — every build is scoped and shipped with governance, access, and traceability in mind.

Book a Data Engineering Talent Match Call

We’ll map your requirements, timelines, and tech stack - and send 2 reference CVs of vetted data engineers.

Industries We Support

Discover Your Use Case
Data Engineering Talent That Delivers Across Regulated, Real-Time, and AI-Driven Domains
Discover Your Use Case

Healthcare & Life Sciences

Build PHI-compliant data pipelines for care, claims, trials, and R&D - with audit-ready traceability and validation.

Enterprise SaaS

Scale telemetry, usage, and multi-tenant analytics pipelines - without compromising performance or visibility.

Pharma & Medtech

Enable secure data movement across trial ops, manufacturing, and AI models - governed and reproducible.

Financial Services

Implement audit-safe, high-throughput pipelines for risk models, compliance reporting, and real-time fraud detection.

Retail & Supply Chain

Deploy real-time ingest and structured datasets for demand forecasting, fulfillment, and pricing models.

Manufacturing

Ingest sensor and production data with streaming and time-series-aware design - optimized for ML and operational dashboards.

Perspectives

Explore
Real-world learnings, bold experiments, and large-scale deployments—shaping what’s next
in the pivotal AI era.
Explore
Blog

AI in Software Development

AI is re-architecting the SDLC. Learn how copilots, domain-trained agents, and intelligent delivery loops are defining the next chapter of software engineering.
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Case Study

Building a Holistic Care Delivery System using AWS for a $30B Healthcare Device Leader

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Playbook

CXO's Playbook for Gen AI

This executive-ready playbook lays out frameworks, high-impact use cases, and risk-aware strategies to help you lead Gen AI adoption with clarity and control.
Read more
Blog

Monolith to Microservices: A CTO's Guide

Explore the pros, cons, and key considerations of Monolithic vs Microservices architecture to determine the best fit for modernizing your software system.
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Case Study

AI-Powered Clinical Trial Match Platform

Accelerating clinical trial enrollment with AI-powered matching, real-time predictions, and cloud-scale infrastructure for one of pharma’s leading players.
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Blog

The Cloud + AI Nexus

Discover why businesses must integrate cloud and AI strategies to thrive in 2025’s fast-evolving tech landscape.
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Blog

Understanding the Role of Agentic AI in Healthcare

This guide breakdowns how the integration of Agentic AI enhances efficiency and decision-making in the healthcare system.
Read more
View All

Hire Data Engineers Who Ship From Week 1
Not 6 Weeks After Documentation Catch-Up

What Happens When You Reach Out:
We assess your project scope, stack, and engagement model
You choose: individual engineer or augmented delivery pod
We send 2 reference CVs from teams that have delivered in regulated, ML-driven, and mission-critical environments
Trusted partner of the world’s most forward-thinking teams.
Tell us a bit about your business, and we’ll get back to you within the hour.

FAQs About Hiring a Data Engineer

Can I interview and screen the engineer before onboarding?

Yes. We support full technical vetting, interviews, and mutual alignment checks before deployment.

What skillsets do your engineers typically bring?

Pipeline development (ETL/ELT), Airflow, dbt, Spark, Snowflake, BigQuery, Redshift, Kafka, data modeling, observability, and governance integration — all built for ML and analytics usage.

How quickly can I get someone started?

In as little as 3–5 business days, we can deploy a vetted engineer aligned to your tech stack and project needs.

Do you offer US-based engineers?

Yes. We have availability for US In-Office, US Remote, and Global Remote depending on your requirement and security posture.

Can they plug into my team or run independently?

Both. We offer embedded engineers and full delivery pods with PM, QA, and data architects if you prefer autonomous execution.