Data Engineer

Full-Time W2 from Day One | Start in Atlanta, Then Travel the U.S. | Housing & Relocation Covered. From day one of training, you're a full-time W2 employee. Not a student. Not an intern. A data engineer. We're hiring a Data Engineer to start in Atlanta, Georgia, and then work on client-facing projects for Fortune 500 companies across the United States. If you have 1+ year of professional experience in Python, SQL, data processing, or software development , this opportunity can help you accelerate your career through hands-on enterprise consulting experience. We're looking for candidates who enjoy working with data, building data pipelines, automating workflows, and developing reliable data solutions. If you have a strong programming foundation and want to grow your skills in cloud data engineering, analytics, and AI-driven data platforms, we'd love to hear from you. Compensation and Benefits. Your hourly rate goes up as you bill hours (details below). Health, dental, and vision insurance. Corporate housing and relocation covered. 401(k) eligibility after one year. Dedicated support team and mentorship. Performance bonuses. 20+ years of placement expertise behind you. Your Pay Grows with Your Billable Hours After 500 billable hours: +$2.00/hr. After 1,000 billable hours: Another +$2.00/hr. Every additional 500 billable hours after that: +$1.00/hr. Where This Role Takes You Hands-on experience building and maintaining enterprise-grade data pipelines. Practical exposure to cloud data platforms across AWS, Azure, and Google Cloud. Experience with data warehousing, ETL/ELT pipelines, and data integration. Opportunities to work with modern technologies such as Python, SQL, Spark, Databricks, Snowflake, and Airflow, depending on project requirements. Exposure to data engineering for analytics, machine learning, and AI applications. A professional network of engineers working across enterprise technology environments. What You'll Do Data Pipeline Development: Build, test, and maintain data pipelines to collect, process, transform, and deliver data from multiple sources. Python Programming: Write scripts and reusable code to automate data processing, validation, and integration tasks. SQL & Databases: Write SQL queries, perform joins and aggregations, and work with relational databases to extract and transform data. ETL/ELT Development: Assist in developing workflows that extract, transform, and load data into data warehouses and analytics platforms. Data Cleaning & Validation: Identify data quality issues, remove duplicates, handle missing values, and ensure data accuracy and consistency. Cloud Data Engineering: Work with cloud storage, databases, and data processing services on AWS, Azure, or Google Cloud. Data Warehousing: Support data modeling, schema design, and the organization of data for reporting and analytics. API & Data Integration: Connect to REST APIs, process JSON data, and integrate information from different applications and systems. Performance Optimization: Help troubleshoot pipeline failures, improve query performance, and optimize data processing workflows. Version Control: Use Git for source control, branching, code reviews, and team collaboration. Documentation & Collaboration: Work with senior data engineers, analysts, software developers, and business stakeholders to deliver reliable data solutions. What You Bring Bachelor's degree in Computer Science, Information Systems, Data Science, Engineering, Mathematics, or a related technical field. At least 1 year of professional experience in data engineering, Python development, SQL development, data analytics, or a related technical role. Proficiency in Python or another programming language used for data processing. Strong SQL fundamentals, including joins, aggregations, filtering, and data manipulation. Understanding of relational databases, data structures, and basic data modeling concepts. Familiarity with APIs, JSON, and working with structured or semi-structured data. Understanding of ETL/ELT concepts and data pipeline fundamentals. Familiarity with Git and collaborative development practices. Strong analytical thinking, problem-solving, and troubleshooting skills.Willingness to learn new technologies and work on enterprise client projects. Bonus Points (Not Required) Hands-on experience with AWS, Microsoft Azure, or Google Cloud Platform. Familiarity with Apache Spark, PySpark, or distributed data processing. Exposure to Snowflake, Databricks, Amazon Redshift, BigQuery, or Azure Synapse Analytics Exposure to machine learning data preparation or AI/LLM data pipelines. Relevant cloud certifications, including AWS Cloud Practitioner, Azure Fundamentals (AZ-900), or Google Cloud certifications. An active GitHub profile showcasing Python scripts, SQL projects, ETL pipelines, or data engineering projects. Location and relocation: You'll start in Atlanta, GA, then travel to client project sites across the United States. Projects typically last 3 to 6 months, and some run a year or longer. Corporate housing and relocation are covered, so you can build your résumé across different industries and cities without the moving costs. Ready to grow your AI career and your paycheck? #J-18808-Ljbffr Tech Consulting