Van Data Team

Data Pipeline Development Services: Hire ETL & Streaming Engineers

Data pipeline debugging and ETL development

Van Data Team provides expert data pipeline development services, engineering scalable, production-grade ETL/ELT pipelines with Airflow, dbt, and Kafka. Streamline your data integration and ship in 2 to 6 weeks with total ownership. Trusted by 150+ global brands across 15+ countries.

Book a Free 30-Min Strategy CallView Data Pipeline Case Studies

Is Your Data Pipeline Holding the Business Back?

Pipelines That Silently Break

Finding out the pipeline failed when the CEO Slacks you a stale dashboard at 8 AM.

Fragile Legacy Scripts

A 4 year old Python and cron stack nobody on the current team dares to touch.

Off-the-Shelf Templates

A generic data stack that doesn't match how your business actually models revenue, users, or events.

Not Production-Grade

Pipelines that work in staging but miss SLAs, skip retries and have no runbook.

Complex to Maintain

500-line SQL scripts, tangled Airflow DAGs, undocumented transformations. Every change is a gamble.

Data Silos Everywhere

Salesforce, Stripe, Mixpanel and NetSuite. Six tools plus six versions of "active customers".

What Every Global Data Pipeline We Deliver Includes

Modular Airflow DAGs, sensible task grouping, deferrable operators where they matter. Code a new engineer can read in an afternoon.

dbt structures tailored to how your business actually thinks about customers, revenue and events. We deliver custom logic instead of generic ecommerce templates.

Secrets in Secret Manager or KMS, least-privilege IAM, encrypted at rest and in transit. Audit-ready from day one.

Correct materialization strategy, partitioning and clustering. Query performance tuned before you see a single dashboard.

Data ingestion from Salesforce, HubSpot, NetSuite, Stripe, Shopify and Segment. Plus custom connectors for rare APIs.

Great Expectations on ingestion, dbt tests on transformation, schema contract enforcement at source boundaries.

Our secret to zero-fail data pipelines? The Founder-Led Execution Loop.

Book a Free 30-Min Data Architecture Review

What You Actually Want

50% Less Firefighting Time

Your engineers stop tailing Airflow logs at midnight and get back to shipping features.

Real-Time Decisions on Trusted Data

Pipelines that run every 15 minutes instead of every 24 hours, with numbers the finance team stops second-guessing.

Pipelines That Just Run

SLA alerts, automatic retries, schema validation, full observability. You see green, not red.

AI-Ready Data Infrastructure

Versioned schemas, semantic layer, clean customer IDs. Your next ML or RAG project starts on week one, not week twelve.

Ready to see these outcomes in your own stack? Let's start with a data architecture review.

Book a Free 30-Minute Data Architecture Review

Our Clients: Who Benefits from Van Data Team's Data Pipeline Development Services?

Data & Analytics Teams

Data & Analytics Teams

You have analysts who write solid SQL, but no one owns the orchestration layer. We handle the infrastructure side so your analysts stay focused on analytics.

Startups & Scale-Ups

Startups & Scale-Ups

Series A through Series C. You've outgrown spreadsheets. Your first data engineer needs a working warehouse and pipelines on day one, not three months of setup.

AI & ML Teams

AI & ML Teams

You're training models, building RAG systems or running AI agents. Clean data is the bottleneck. We've built ingestion and transformation for teams working on 400K+ document RAG systems, healthcare lab pipelines and agentic workflows.

Teams Replacing Legacy ETL

Teams Replacing Legacy ETL

You inherited a pile of cron-triggered Python scripts or a 4-year-old SSIS package. We migrate with parallel runs and delta validation. No big-bang cutovers.

Our Data Pipeline Development Process

A 60 minute technical call to map sources, destinations, and SLAs. We profile real data in a dev warehouse for 3 to 5 days, then deliver a written scope document covering inclusions, timeline, and risks.

  • Map source systems, destinations, and data SLAs
  • Profile real data in a dev warehouse for 3 to 5 days
  • Deliver written scope document with inclusions, timeline, and risks

A one page architecture diagram plus a decision log explaining every tool choice. Why Apache Airflow over Prefect. Why BigQuery over Snowflake. You sign off before any infrastructure spins up.

  • Architecture diagram with tool decision log
  • Clear rationale for every technology choice
  • Client sign-off before any infrastructure spins up

Week one ships a working skeleton. We scaffold DAGs, sample dbt models, and infrastructure as code in a dev environment. By Friday, one pipeline runs end to end, surfacing IAM and networking issues while fixes stay cheap.

  • Scaffold DAGs, sample dbt models, and IaC in dev
  • One pipeline runs end-to-end by end of week one
  • Surface IAM and networking issues while fixes are cheap

Weekly sprints with Monday demos. All code pushes to a client owned GitHub repository. Feedback tracked in Linear or GitHub Issues. No vendor blackouts, no surprise pull requests at final delivery.

  • Weekly sprints with Monday demos
  • All code in your GitHub repository
  • Feedback tracked in Linear or GitHub Issues

A full backfill with row by row reconciliation against source systems. dbt tests cover nulls, uniqueness, and referential integrity. Great Expectations enforces schema contracts at ingestion. You get a written validation report before launch.

  • Full backfill with row-by-row reconciliation
  • dbt tests for nulls, uniqueness, and referential integrity
  • Great Expectations schema contract enforcement
  • Written validation report before launch

Parallel runs against legacy systems for 5 to 10 business days, then cutover during business hours. Handoff includes a runbook, dbt docs, architecture diagrams, and a 90 minute recorded walkthrough. Plus 30 days of free post launch support.

  • Parallel runs against legacy systems for 5 to 10 business days
  • Runbook, dbt docs, architecture diagrams, and recorded walkthrough
  • 30 days of free post-launch support included

What Makes Van Data Team Different

Starting timeline
Van Data Team2–6 weeks
Typical Freelancer4–12 weeks
Large Agency8–16 weeks
Production reliability checklist
Van Data TeamProprietary 40-point
Typical FreelancerAd-hoc
Large AgencyVaries
Idempotent DAG design
Van Data Team✔️
Typical FreelancerSometimes
Large Agency✔️
Schema contract enforcement
Van Data TeamGreat Expectations + dbt
Typical Freelancer✗
Large Agency✔️
SLA alerts to PagerDuty/Opsgenie
Van Data Team✔️
Typical FreelancerRare
Large Agency✔️
Runbook and recorded handoff
Van Data Team✔️
Typical Freelancer✗
Large Agency✔️
Direct access to the builders
Van Data TeamEvery meeting
Typical Freelancer✔️
Large AgencyRare past kickoff
You own the GitHub repo
Van Data Team✔️
Typical FreelancerVaries
Large Agency✔️
Multi-source stack experience
Van Data Team150+ projects
Typical FreelancerVaries
Large Agency✔️
Free 30 days post-launch support
Van Data Team✔️
Typical Freelancer✗
Large AgencyVaries
Airflow + dbt + streaming expertise in one team
Van Data Team✔️
Typical FreelancerRare
Large Agency✔️ at 3–5x cost

Why Global Clients Trust Data Pipeline Development Services from Van Data Team

Our Proprietary Reliability Checklist

Every pipeline we ship passes the same 40-point production-readiness checklist: idempotency, schema validation, SLA alerts, retry policies, runbook coverage and lineage. Used on 150+ engagements. Not available from any other vendor.

Multi-Industry Experience

We've shipped production work in healthcare analytics, fintech, aviation data, e-commerce, logistics and SaaS. Each industry has its own data shape quirks. We've seen most of them.

Easy to Manage After Handoff

Everything ships with a runbook, README, dbt docs, architecture diagram and a 90-minute recorded handoff session. Your on-call engineer can work from documentation alone.

Built for AI Workloads

Every pipeline we design today is designed with feature engineering, embeddings and agent consumption patterns in mind. When your team ships the next LLM workflow, the data is already ready.

Meet Van Data Team – Your Partners in Automated Data Pipeline Development Services

With 5+ years of production data engineering experience and 150+ projects shipped across industries, Van Data Team is a specialist consultancy providing data pipeline development services that run reliably in production. We use a proprietary reliability checklist refined across projects in healthcare, fintech, ecommerce, logistics and SaaS. We serve clients primarily in the US, UK, EU and Australia, with Top Rated Plus status and a 100% Job Success Score on Upwork.

Tran Tien Van - Founder of Van Data Team
FeatureReliability Standard
✅ Production-Grade⭐ Reliable from day one
✅ Full Observability⭐ Alerts before you notice
✅ You Own the Stack⭐ Your GitHub, your cloud
✅ Custom-Built⭐ Not a reskinned template
Meet Van Data Team

What Clients Say About Our Data Pipeline Development Services

Van Data Team builds production-ready AI agents and agentic AI systems that automate real workflows, control operational costs, and scale with your business.

Verified review signal

5.0

71 reviews on Upwork

5 stars
69
4 stars
2
3 stars
0
2 stars
0
1 star
0
See Upwork Reviews
CS

Chod S.

5.00

February 25, 2026

Data Extraction & Automation Engineer for Large Document Repository

Verified rating captured from the shared Upwork review screenshots.

CK

Chris K.

5.00

December 30, 2025

FT Platform Phase #2

"Great backend developer, highly recommend!"
GB

Gilad B.

5.00

December 18, 2025

Phase 0: Design a granular data schema and structure, and full tool flow

"Very knowledgeable and professional. Good communication"
CK

Chris K.

5.00

December 5, 2025

BQ Pipeline Automation + Lightweight API

Verified rating captured from the shared Upwork review screenshots.

AB

Ari B.

5.00

November 25, 2025

30 minute consultation

Verified rating captured from the shared Upwork review screenshots.

TS

Tomer S.

5.00

September 9, 2025

Data handling

Verified rating captured from the shared Upwork review screenshots.

JD

Julio D.

5.00

July 16, 2025

Web scraper in R

"Tran was great, very knowledgeable and quick responses"
JY

Jason Y.

5.00

June 13, 2025

Flowise N8N AI Agent Builder

Verified rating captured from the shared Upwork review screenshots.

AP

Adam P.

5.00

May 26, 2025

scrape data for research project

Verified rating captured from the shared Upwork review screenshots.

DM

Dillon M.

5.00

May 16, 2025

30 minute consultation

Verified rating captured from the shared Upwork review screenshots.

BV

Bernard V.

5.00

May 12, 2025

30 minute consultation

Verified rating captured from the shared Upwork review screenshots.

PT

Preska T.

5.00

April 10, 2025

LLM

Verified rating captured from the shared Upwork review screenshots.

MM

Madison M.

5.00

March 31, 2025

Review Git Pull Requests

"Very responsive and quick to get started! Produced excellent results. I will definitely reach out again in the future."
DC

David C.

5.00

March 29, 2025

You will get AWS, GCP and Azure Data pipeline

"Great platform to interface with developer."
AJ

Alex J.

5.00

February 18, 2025

You will get Data Scraping | Data Extraction | Web Scraper | Automation Tools

"Fast, responsive, professional. Really appreciated the thorough documentation too."
TS

Tomer S.

5.00

December 12, 2024

Create Web scraper for Facebook

"Van exceeded all expectations with exceptional professionalism and expertise. They delivered high-quality work ahead of schedule, communicated effectively throughout the project, and made the collaboration seamless and enjoyable. I highly recommend Van to anyone looking for a skilled and reliable freelancer."
PT

Preska T.

5.00

October 21, 2024

You will get Data Scraping | Data Extraction | Web Scraper | Automation Tools

"I recently had the pleasure of working with Tran, and I can't express enough how impressed I am with his work. From the very beginning, he demonstrated a deep understanding of our project requirements and brought a level of expertise that made a significant difference in the outcome. What truly sets Tran apart is his commitment to excellence."
AW

Alice W.

5.00

June 28, 2024

Data Pipeline

Verified rating captured from the shared Upwork review screenshots.

AW

Alice W.

5.00

May 26, 2024

Admin Panel for Data Management

"AMAZING. We are lucky that we found Van. He helped us with our database structure. He is very knowledgeable and very cooperative. We are still continuing to work with him further. I can only highly recommend."
NS

Nic S.

5.00

May 15, 2024

Web scraping - Project review and proposal

"Excellent work. I'd be very happy to work with Tran in the future."
PK

Paris K.

5.00

March 22, 2024

Seeking developers experienced with LAMP (Python) and REST APIs for UX Research Study / gstd-2024-1

"Tran did a great job on a LAMP REST API deployment to Microsoft Azure. We'd be happy to work with this freelancer again."
YK

Yalcin K.

5.00

March 18, 2024

Python Developer to Build a Shopify Integration

"Van is a great data engineer, and I highly recommend it. He joined our project and helped build a custom data pipeline within weeks."
OD

Omer D.

4.80

March 5, 2024

Attach Stripe webhook to Flask server

Verified rating captured from the shared Upwork review screenshots.

Meet the Engineers Who Build Your Pipeline

Tran Tien Van - Founder of Van Data Team

Engineers Who Understand the Business, Not Just the Code

Our team has shipped production data work for founders, CFOs and analytics leads. We translate business questions into pipeline design decisions, not the other way around.

Multi-Industry Engineering Experience

500+ technical deliverables across healthcare analytics, aviation, fintech, logistics, e-commerce and SaaS. We've seen most data shape patterns. We know which ones bite at scale.

Handoff-Ready from Day One

Every pipeline we ship is designed to be owned by your team within 30 days. Our handoff checklist is as rigorous as our build checklist.

150+ Companies Have Chosen VANDATATEAM

VanDataTeam is proud to partner with 150+ leading companies across 15+ countries, building lasting success through production-grade AI Agent systems and data engineering expertise.

  • Ahrvo logo

    Ahrvo

    Client

  • Athenahealth logo

    Athenahealth

  • Clarify IQ logo

    Clarify IQ

  • Cleargen logo

    Cleargen

  • Conversion Finder logo

    Conversion Finder

  • Debit My Data logo

    Debit My Data

  • Ellipsis Earth logo

    Ellipsis Earth

    Client

  • Finance Scaler logo

    Finance Scaler

  • Forskningslogen Friederich Munter logo

    Forskningslogen Friederich Munter

  • HBC logo

    HBC

  • Hello Alma logo

    Hello Alma

  • Hudson's Bay Company logo

    Hudson's Bay Company

  • Kejora logo

    Kejora

  • Kiki AI logo

    Kiki AI

  • Lunada logo

    Lunada

  • OBJX logo

    OBJX

  • Praxis AI logo

    Praxis AI

    Client

  • Rarity Capital logo

    Rarity Capital

  • Re Talk Py logo

    Re Talk Py

  • Setmore logo

    Setmore

  • Stock Exploit logo

    Stock Exploit

  • Supply Bridge logo

    Supply Bridge

  • Thrive 5 IR logo

    Thrive 5 IR

  • Voodoo logo

    Voodoo

    Client

  • Wajooba logo

    Wajooba

  • White Ribbon Alliance logo

    White Ribbon Alliance

  • With Words logo

    With Words

  • You Heal logo

    You Heal

    • What Happens After Your Pipeline Goes Live

    Included with Every Project

    • 30 to 60 days of post-launch support at no cost
    • Bug fixes, tuning and team questions covered
    • Full source code ownership from day one
    • Infrastructure in your own cloud accounts
    • Complete documentation package

    Optional Monthly Retainer

    • 10 to 40 hours per month
    • Pipeline monitoring and on-call coverage
    • Quarterly architecture reviews
    • Net-new source additions
    • No minimum past the first month

    Frequently Asked Questions

    The average cost for data pipeline development at Van Data Team typically ranges from $500 to $2,000 for standard implementations. For large-scale enterprise projects with complex architectures, we offer custom packages starting at $4,000. The final investment varies based on data sources, transformation complexity, and required latency.

    A data pipeline is production-grade when a new engineer can be paged at 3 AM, open the runbook and fix the issue without calling the person who built it. Concretely, that means idempotent DAG design, schema contract enforcement, SLA alerts, retry policies with exponential backoff and lineage documentation.

    Most pipelines take 2 to 6 weeks from kickoff to go live. Simple builds on existing infrastructure finish in 2 to 3 weeks. Full multi-source pipelines with dbt, Airflow and monitoring take 4 to 6 weeks. Streaming or multi-region deployments run 6 to 12 weeks.

    Our default stack: Apache Airflow for orchestration, dbt for SQL transformation, Airbyte for common-source ingestion, custom Python for rare APIs, BigQuery or Snowflake as the warehouse, Great Expectations for data quality, Datadog or Grafana for monitoring. For streaming: Apache Kafka or Google Pub/Sub. We ship on GCP, AWS and Azure.

    Nope, roughly 35% of our engagements start from the ground up. Van Data Team manages the full stack setup including cloud configuration, warehouse provisioning and expert tool selection. For established infrastructures we integrate into your environment to optimize and scale your existing data operations.

    Yes. That's the goal. Every pipeline ships with a runbook covering common failures, a README per repo, dbt docs published to a URL, an architecture diagram and a recorded 90-minute handoff session. If your team has basic Python and SQL skills, they can maintain the pipeline independently.

    Our sales cycle is intentionally short. After an initial 30-minute architecture review, we deliver a written scope and quote within 24 to 48 hours. Once approved, development begins within 3 to 5 business days. Simple pipelines go live in 2 to 3 weeks.

    Every project includes 30 days of free post-launch support. After that, you have three options: maintain in-house using the documentation, engage us hourly for one-off fixes, or move to a monthly retainer. Most clients handle maintenance in-house after month two.

    Yes. We serve clients primarily in the US, UK, EU and Australia, spanning 15+ countries to date. Engagements are fully remote, with time zone overlap handled through async Slack and Linear plus weekly sync calls in the client's working hours.

    Van Data Team is tool agnostic. Whether you run Prefect instead of Airflow or Redshift instead of BigQuery we build to your specifications. We only recommend tool changes if we can mathematically prove reduced costs or improved reliability in an architecture decision log.

    Our Team Is Ready to Help

    After you reach out we respond within 24 hours to schedule a scoping call. Bring your current pipeline stack, a list of sources and three problems you want solved. We deliver a written recommendation and rough timeline. No deck and no pressure.

    Tran Tien Van, Founder of Van Data Team, ready to help