Data Engineer

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. Apply Now Refer to a Friend Tech Consulting