| Title: | Jr. Data Engineer |
|---|---|
| ID: | TC- 106 |
| Location: | Nationwide |
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:
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Have 1+ year of professional coding experience — Python and SQL used regularly at work
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Understand data at a technical level — queries, schemas, pipelines, not just dashboards
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Know OOP concepts and can write structured, maintainable code
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Have exposure to cloud platforms or big data tooling — even at a basic level
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Are ready to go deep on AI/ML engineering, not just learn the buzzwords
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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.
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✓ Full-time W2 salary from day one |
✓ Health, dental & vision insurance |
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✓ Corporate housing & relocation covered |
✓ 401(k) eligibility after one year |
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✓ Fortune 1000 client exposure |
✓ Dedicated support team & mentorship |
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✓ Performance bonuses |
✓ 25+ years of placement expertise behind you |
What you will learn in 9 weeks
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Data engineering & big data
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Cloud platforms & AI tooling
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Program timeline
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Weeks 1–2 |
Python, SQL, and data engineering foundations — pipelines, APIs, and OOP at scale |
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Weeks 3–4 |
Big Data tooling — Spark, Kafka, Airflow, Hadoop, Hive, and cloud data platforms |
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Weeks 5–6 |
Cloud data warehousing — Snowflake, BigQuery, AWS/Azure/GCP data services |
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Weeks 7–8 |
Advanced pipelines, streaming architectures, DevOps, CI/CD, and data security |
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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
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Python: 1+ year of Python as a core part of your job — scripts, pipelines, automation, or data processing
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SQL: Proficient SQL — JOINs, aggregations, subqueries, and working with real databases professionally
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Data: Hands-on data wrangling experience — cleaning, transforming, and handling messy real-world datasets
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Git: Git version control in a team environment — branching, pull requests, and collaborative workflows
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APIs: REST API experience in Python — hitting endpoints, parsing JSON, handling authentication
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OOP: Solid understanding of OOP — classes, inheritance, interfaces used in real production code
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Stats: Basic statistics — distributions, mean/median/std dev, and understanding what data is telling you
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Location: Willingness to relocate to Atlanta, GA for training and travel to client sites for project placements
Highly preferred — fast-tracks your application
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Big data tooling exposure: Spark, Kafka, Airflow, Hadoop, Hive, or Flink
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Cloud platform experience: AWS, Azure, or GCP — especially data or storage services
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Data warehouse or BI tool experience: Snowflake, BigQuery, Tableau, or Power BI
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NoSQL database experience: MongoDB, Cassandra, DynamoDB, or similar
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DevOps basics: CI/CD pipelines, Docker, or containerized data environments
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Active GitHub profile with Python scripts, ETL projects, or data pipeline work
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Familiarity with data governance, GDPR, HIPAA, or security compliance requirements
Education
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Bachelor's degree in Computer Science, Data Science, Software Engineering, Mathematics, Statistics, or a related quantitative field
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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:
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Real enterprise data pipeline and warehouse experience — not toy datasets
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Hands-on big data and cloud engineering skills most engineers are still self-teaching
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Verifiable Fortune 1000 consulting experience on your resume
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A peer network of engineers who went through the same intensive program
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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 the 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.
