How to DIY: Data Engineer

My data from Stripe, Salesforce, my app database, and 7 other tools cleaned, unified, and available in one place for analytics — without building custom scripts that break every Tuesday

DIY Difficulty🔥Hard DIY
Save up to $5,000-15,000+/mo by doing it yourself
HardDifficulty
2-4 monthsTime to Learn
$0-200/moDIY Cost
5Steps
2Tools

Tools used in this guide

5
FivetranFree (limited) / $1/creditGoogle BigQueryFree (1TB queries/mo) / Pay-per-querydbt CloudFree (1 developer) / $100/moMetabaseFree (self-hosted) / $85/mo (cloud)dbt TestsIncluded in dbt

How to DIY: Data Engineer

A step-by-step guide to doing this yourself — honestly.

Easy
Medium
Hard

What you're really trying to do

My data from Stripe, Salesforce, my app database, and 7 other tools cleaned, unified, and available in one place for analytics — without building custom scripts that break every Tuesday

DIY Cost

$0-200/mo

2-4 months to learn

Hire Cost

$5,000-15,000+/mo

Done for you

You could save $5,000-15,000+/mo by doing it yourself

Step-by-Step Guide

Follow along at your own pace. Most people finish in 2-4 months.

1

Extract data with Fivetran or Airbyte

~10 min

Fivetran connects to 300+ data sources (Stripe, Shopify, Salesforce, databases, APIs) and syncs them to your warehouse automatically. Airbyte is the open-source alternative. Set up connectors in the UI — no code needed for standard sources.

FivetranFree (limited) / $1/credit
2

Store data in BigQuery or Snowflake

~10 min

BigQuery (Google) or Snowflake are cloud data warehouses that scale automatically. BigQuery is simpler and cheaper for small-medium workloads. Load your data here — it's the central hub everything else queries from. BigQuery's free tier covers 1TB of queries/month.

Google BigQueryFree (1TB queries/mo) / Pay-per-query
3

Transform data with dbt

~10 min

dbt (data build tool) lets you write SQL transformations that run against your warehouse. Define models that clean, join, and aggregate your raw data into analysis-ready tables. dbt Cloud has a free tier with a visual IDE and scheduled runs.

dbt CloudFree (1 developer) / $100/mo
4

Visualize with Metabase

~15 min

Metabase connects to your data warehouse and lets you build dashboards without SQL. Point it at your dbt models and create charts, tables, and reports. Self-hosted is free; cloud is $85/month. It's the simplest BI tool that non-technical team members can actually use.

MetabaseFree (self-hosted) / $85/mo (cloud)
5

Monitor data quality

~15 min

Add dbt tests to validate your data: not null checks, unique constraints, accepted values, and custom SQL tests. dbt runs these automatically and alerts you when data quality degrades. Bad data in, bad decisions out — testing catches problems before they reach your dashboards.

dbt TestsIncluded in dbt

When to hire instead

Hire when: you need real-time streaming pipelines (not just daily/hourly batch syncs), you're joining data across 10+ sources with complex business logic, your data infrastructure needs to support ML model training, or data quality issues are leading to wrong business decisions that cost real money. A data engineer builds the guardrails that prevent 'our revenue numbers are off by 30%' moments.

No time? Skip to hiring

Real talk

The modern data stack (Fivetran + BigQuery + dbt + Metabase) has made basic data engineering accessible to anyone comfortable with SQL. If your needs are 'pull data from Stripe, Salesforce, and our app database, clean it up, and make dashboards,' you can genuinely DIY this in a weekend. The complexity spikes when you need real-time processing, complex joins that require understanding slowly changing dimensions, or data that feeds production systems (reverse ETL). Start simple, and you'll know when you've outgrown DIY because things will start breaking.

Our Verdict

DIYHIRE
It depends

Difficulty

hard

Learning time

2-4 months

DIY cost

$0-200/mo

Hire cost

$5,000-15,000+/mo

Choose DIY if...

  • 2 of 2 tools are free
  • You want to learn a new skill
  • Budget matters more than time

Choose Hire if...

  • The learning curve is steep
  • You need professional-quality results
  • Your time is worth more than the cost
  • You have a tight deadline

Learn from video tutorials

Sometimes watching is easier than reading. Search for tutorials:

YouTube tutorialsTikTok guides

Join the conversation

See what other people are saying about doing this yourself:

RedditQuora

Prefer to hire a pro?

No shame in that. Sometimes your time is worth more than the money you'd save. These top-rated freelancers specialize in Data Engineer and can get it done fast.

Vetted profilesFiverr & UpworkStarting at $5,000-15,000+/mo
A
#1 Best Pick
Top Rated
From
$180
Fiverr

Alex G

@datapipe_alex · Top Rated

Best for: Best overall — data pipeline engineer specializing in ETL, Airflow, and dbt
4.9(156+ reviews)7d delivery
Pros
Expert in modern data stack: dbt, Airflow, Snowflake
Builds reliable, well-monitored data pipelines
Strong SQL and Python data engineering skills
Cons
Data engineering focus — not data science or ML
Complex pipelines require extended timelines
View on Fiverr
Y
#2 Runner Up
Top Rated
From
$200
Fiverr

Yuki M

@bigdata_yuki · Level 2

Best for: Best for big data — Spark and Databricks specialist for large-scale data processing
4.8(89+ reviews)10d delivery
Pros
Deep expertise in Spark, Databricks, and distributed systems
Handles terabyte-scale data processing
Good at optimizing slow queries and reducing compute costs
Cons
Focused on big data — may be overkill for small datasets
Longer delivery times for complex data architectures
View on Fiverr
T
#3 Top 3
PRO
From
$2500
Fiverr Pro

Toptal Data Engineers

@toptal · Top 3%

Best for: Best for enterprise — senior data engineers for building data platforms and warehouse architectures
4.9(195+ reviews)5d delivery
Pros
Pre-vetted senior data engineers with platform-building experience
Can design entire data infrastructure from scratch
Experience with data governance and compliance requirements
Cons
Premium pricing at $2,500+/week
Requires clear data strategy for effective engagement
View on Fiverr Pro
Browse all Data Engineer freelancers

Frequently Asked Questions

Can I really do data engineer myself?▼
Yes. The difficulty is hard — it's challenging and requires dedication to learn properly. Expect to spend about 2-4 months learning the basics. The DIY route costs around $0-200/mo, compared to $5,000-15,000+/mo if you hire a freelancer.
What tools do I need for DIY data engineer?▼
The main tools are: Fivetran, Google BigQuery, dbt Cloud, Metabase, dbt Tests. 4 of these are free to use. Our step-by-step guide above walks you through exactly how to use each one.
How long does it take to learn data engineer?▼
Plan for about 2-4 months to get comfortable with the basics. 5 steps cover the full process from start to finish. After your first project, subsequent ones go much faster.
When should I hire a data engineer instead of doing it myself?▼
Hire when: you need real-time streaming pipelines (not just daily/hourly batch syncs), you're joining data across 10+ sources with complex business logic, your data infrastructure needs to support ML model training, or data quality issues are leading to wrong business decisions that cost real money. A data engineer builds the guardrails that prevent 'our revenue numbers are off by 30%' moments.
Is it worth paying $5,000-15,000+/mo for a freelancer vs doing it myself for $0-200/mo?▼
The modern data stack (Fivetran + BigQuery + dbt + Metabase) has made basic data engineering accessible to anyone comfortable with SQL. If your needs are 'pull data from Stripe, Salesforce, and our app database, clean it up, and make dashboards,' you can genuinely DIY this in a weekend. The complexity spikes when you need real-time processing, complex joins that require understanding slowly changing dimensions, or data that feeds production systems (reverse ETL). Start simple, and you'll know when you've outgrown DIY because things will start breaking. If your time is worth more than the difference and you need professional results fast, hiring makes sense. If you enjoy learning and have 2-4 months to invest, DIY is a great option.
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