Data Engineer
Big Data & AI Bootcamp · Atlanta, GA · Full-Time W2 Employment
Stop waiting for the right opportunity. In 9 weeks, go from data-aware developer to a fully deployed Data Engineer — paid from day one, trained on real tools, and placed on Fortune 1000 client projects.
Who this is for
You already write code. You work with data. You know SQL and Python aren't just buzzwords — they're tools you use daily. What you haven't had yet is the structured path to go from writing scripts and queries to engineering the data pipelines, warehouses, and big data systems that power real enterprise operations.
This program is built for IT professionals who:
Have 1+ year of professional coding experience — Python and SQL used regularly at work
Understand data at a technical level — queries, schemas, pipelines, not just dashboards
Know OOP concepts and can write structured, maintainable code
Have exposure to cloud platforms or big data tooling — even at a basic level
Are ready to go deep on AI/ML engineering, not just learn the buzzwords
Are willing to relocate to Atlanta, GA for training and to client sites for project assignments
What you get
From day one of training, you are a full-time W2 employee. Not a student. Not an intern. A Data Engineer.
✓ Full-time W2 salary from day one
✓ Health, dental & vision insurance
✓ Corporate housing & relocation covered
✓ 401(k) eligibility after one year
✓ Fortune 1000 client exposure
✓ Dedicated support team & mentorship
✓ Performance bonuses
✓ 25+ years of placement expertise behind you
What you will learn in 9 weeks
Data engineering & big data
Apache Spark, Hadoop, Hive, Kafka & Airflow pipelines
Snowflake, BigQuery, and modern cloud data warehousing
ETL/ELT pipeline design, orchestration, and optimization
Batch and real-time streaming data architectures
Data modeling, schema design, and governance best practices
Docker, Kubernetes, and containerized data workflows
Cloud platforms & AI tooling
AWS, Azure, and GCP — data and ML services
CI/CD pipelines and DevOps for data engineering
NoSQL databases: MongoDB, Cassandra, and DynamoDB
Data security, GDPR, HIPAA, and compliance requirements
AI-assisted development with GitHub Copilot & Claude AI
Agile, Scrum, and enterprise delivery workflows
Program timeline
Weeks 1–2
Python, SQL, and data engineering foundations — pipelines, APIs, and OOP at scale
Weeks 3–4
Big Data tooling — Spark, Kafka, Airflow, Hadoop, Hive, and cloud data platforms
Weeks 5–6
Cloud data warehousing — Snowflake, BigQuery, AWS/Azure/GCP data services
Weeks 7–8
Advanced pipelines, streaming architectures, DevOps, CI/CD, and data security
Week 9
Client readiness — interview prep, professional skills, and placement support
Required skills & qualifications
We review every resume carefully. Here is exactly what we look for — the more clearly your resume demonstrates these skills, the faster you will move through our process.
Must-have — non-negotiable
Python: 1+ year of Python as a core part of your job — scripts, pipelines, automation, or data processing
SQL: Proficient SQL — JOINs, aggregations, subqueries, and working with real databases professionally
Data: Hands-on data wrangling experience — cleaning, transforming, and handling messy real-world datasets
Git: Git version control in a team environment — branching, pull requests, and collaborative workflows
APIs: REST API experience in Python — hitting endpoints, parsing JSON, handling authentication
OOP: Solid understanding of OOP — classes, inheritance, interfaces used in real production code
Stats: Basic statistics — distributions, mean/median/std dev, and understanding what data is telling you
Location: Willingness to relocate to Atlanta, GA for training and travel to client sites for project placements
Highly preferred — fast-tracks your application
Big data tooling exposure: Spark, Kafka, Airflow, Hadoop, Hive, or Flink
Cloud platform experience: AWS, Azure, or GCP — especially data or storage services
Data warehouse or BI tool experience: Snowflake, BigQuery, Tableau, or Power BI
NoSQL database experience: MongoDB, Cassandra, DynamoDB, or similar
DevOps basics: CI/CD pipelines, Docker, or containerized data environments
Active GitHub profile with Python scripts, ETL projects, or data pipeline work
Familiarity with data governance, GDPR, HIPAA, or security compliance requirements
Education
Bachelor's degree in Computer Science, Data Science, Software Engineering, Mathematics, Statistics, or a related quantitative field
Strong candidates from non-traditional backgrounds with demonstrable Python and data engineering experience are also considered
Why this opportunity stands out
Data engineering is one of the most in-demand specializations in tech right now — and most companies can’t hire fast enough.
Most developers spend years slowly picking up data engineering skills between projects, side reading, and online courses. This program compresses that into 9 weeks of structured, hands-on training across Python, SQL, big data tooling, and cloud platforms — then places you directly on paid engagements with Fortune 1000 clients across finance, healthcare, retail, logistics, and tech.
You will leave with:
Real enterprise data pipeline and warehouse experience — not toy datasets
Hands-on big data and cloud engineering skills most engineers are still self-teaching
Verifiable Fortune 1000 consulting experience on your resume
A peer network of engineers who went through the same intensive program
A clear, supported pathway to senior-level Data Engineer placement
Our clients include:
Microsoft · Google · Johnson & Johnson · Walmart · PayPal · T-Mobile · Capital One · Wells Fargo · Nike · Dell · CVS · Verizon · McDonald’s · Charles Schwab · Fannie Mae · Charter
Ready to apply?
Submit your resume and complete our AI-powered interview for fastest consideration. We review applications on a rolling basis — cohort spots are limited.
Strong English communication skills (written and verbal) are required for all client-facing roles.
Apply today — your next career level starts here.

Data Engineer

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