Job Description

Data EngineerBig Data & AI Bootcamp · Atlanta, GA · Full-Time W2 EmploymentStop 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.This program is built for IT professionals who:Have 1+ year of professional coding experience — Python and SQL used regularly at workUnderstand data at a technical level — queries, schemas, pipelines, not just dashboardsKnow OOP concepts and can write structured, maintainable codeHave exposure to cloud platforms or big data tooling — even at a basic levelAre ready to go deep on AI/ML engineering, not just learn the buzzwordsAre willing to relocate to Atlanta, GA for training and to client sites for project assignmentsFrom 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 insuranceCorporate housing & relocation covered - 401 (k) eligibility after one yearFortune 1000 client exposure - Dedicated support team & mentorshipPerformance bonuses - 25+ years of placement expertise behind youWhat you will learn in 9 weeksData engineering & big dataApache Spark, Hadoop, Hive, Kafka & Airflow pipelinesSnowflake, BigQuery, and modern cloud data warehousingETL/ELT pipeline design, orchestration, and optimizationBatch and real-time streaming data architecturesData modeling, schema design, and governance best practicesDocker, Kubernetes, and containerized data workflows - Cloud platforms & AI toolingAWS, Azure, and GCP — data and ML servicesCI/CD pipelines and DevOps for data engineeringNoSQL databases: MongoDB, Cassandra, and DynamoDBData security, GDPR, HIPAA, and compliance requirementsAI-assisted development with GitHub Copilot & Claude AIAgile, Scrum, and enterprise delivery workflowsProgram timelineWeeks 1–2 - Python, SQL, and data engineering foundations — pipelines, APIs, and OOP at scaleWeeks 3–4 - Big Data tooling — Spark, Kafka, Airflow, Hadoop, Hive, and cloud data platformsWeeks 5–6 - Cloud data warehousing — Snowflake, BigQuery, AWS/Azure/GCP data servicesWeeks 7–8 - Advanced pipelines, streaming architectures, DevOps, CI/CD, and data securityWeek 9 - Client readiness — interview prep, professional skills, and placement supportRequired skills & qualificationsWe 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-negotiablePython: 1+ year of Python as a core part of your job — scripts, pipelines, automation, or data processingSQL: Proficient SQL — JOINs, aggregations, subqueries, and working with real databases professionallyData: Hands-on data wrangling experience — cleaning, transforming, and handling messy real-world datasetsGit: Git version control in a team environment — branching, pull requests, and collaborative workflowsAPIs: REST API experience in Python — hitting endpoints, parsing JSON, handling authenticationOOP: Solid understanding of OOP — classes, inheritance, interfaces used in real production codeStats: Basic statistics — distributions, mean/median/std dev, and understanding what data is telling youLocation: Willingness to relocate to Atlanta, GA for training and travel to client sites for project placementsHighly preferred — fast-tracks your applicationBig data tooling exposure: Spark, Kafka, Airflow, Hadoop, Hive, or FlinkCloud platform experience: AWS, Azure, or GCP — especially data or storage servicesData warehouse or BI tool experience: Snowflake, BigQuery, Tableau, or Power BINoSQL database experience: MongoDB, Cassandra, DynamoDB, or similarDevOps basics: CI/CD pipelines, Docker, or containerized data environmentsActive GitHub profile with Python scripts, ETL projects, or data pipeline workFamiliarity with data governance, GDPR, HIPAA, or security compliance requirementsEducationBachelor's degree in Computer Science, Data Science, Software Engineering, Mathematics, Statistics, or a related quantitative fieldStrong candidates from non-traditional backgrounds with demonstrable Python and data engineering experience are also consideredWhy this opportunity stands outData 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 datasetsHands-on big data and cloud engineering skills most engineers are still self-teachingVerifiable Fortune 1000 consulting experience on your resumeA peer network of engineers who went through the same intensive programA clear, supported pathway to senior-level Data Engineer placementOur clients include:Microsoft · Google · Johnson & Johnson · Walmart · PayPal · T-Mobile · Capital One · Wells Fargo · Nike · Dell · CVS · Verizon · McDonald's · Charles Schwab · Fannie Mae · CharterReady 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.

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