Data Engineer

Advanced Tech Placement; Atlanta (GA); On-site; USD 120,000 - 150,000; Full time

Job summary

Advanced Tech Placement seeks a Data Engineer to design, build, and optimize scalable cloud-based data pipelines and infrastructure. The role focuses on production-ready data solutions using AWS, Databricks, PySpark, SQL, and Python to support analytics, reporting, and business intelligence.

Responsibilities include designing and maintaining pipelines, ETL/ELT, data warehousing, Spark optimization, and CI/CD practices.

Qualifications

• Bachelor's or Master's degree in Computer Science, Statistics, Analytics, or related field.
• 3-5+ years of hands-on Data Engineering experience.
• Strong experience with AWS, Databricks, PySpark, Python, and SQL.
• Experience building and supporting production data pipelines.
• Strong understanding of ETL/ELT, data modeling, and data warehousing.
• Experience with SQL query optimization, Spark performance tuning, and CI/CD.
• Strong troubleshooting, problem-solving, and communication skills.

Responsibilities

• Design, develop, and maintain scalable cloud-based data pipelines using AWS, Databricks, PySpark, Python, and SQL.
• Build and optimize ETL/ELT processes, data models, and data warehousing solutions.
• Optimize Spark and SQL workloads for performance, reliability, and cost efficiency.
• Monitor, troubleshoot, and support production data pipelines.
• Implement CI/CD, automated deployments, unit testing, and code quality standards.
• Collaborate with cross-functional teams to translate business requirements into scalable data solutions.
• Document technical designs, data flows, and processes.

Skills

Data engineering

Cloud data pipelines

ETL/ELT

SQL optimization

Spark performance tuning

CI/CD

Communication

Education

Bachelor's or Master's in CS/Stats/Analytics

Tools

AWS

Databricks

PySpark

Python

SQL

Job description

We are seeking a Data Engineer to design, build, and optimize scalable cloud-based data pipelines and infrastructure. This role will focus on developing production-ready data solutions using AWS, Databricks, PySpark, SQL, and Python to support analytics, reporting, and business intelligence.

Key Responsibilities

• Design, develop, and maintain scalable cloud-based data pipelines using AWS, Databricks, PySpark, Python, and SQL.

• Build and optimize ETL/ELT processes, data models, and data warehousing solutions.

• Optimize Spark and SQL workloads for performance, reliability, and cost efficiency.

• Monitor, troubleshoot, and support production data pipelines.

• Implement CI/CD, automated deployments, unit testing, and code quality standards.

• Collaborate with cross-functional teams to translate business requirements into scalable data solutions.

• Document technical designs, data flows, and processes.

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Statistics, Analytics, or related field.

• 3-5+ years of hands-on Data Engineering experience.

• Strong experience with AWS, Databricks, PySpark, Python, and SQL.

• Experience building and supporting production data pipelines.

• Strong understanding of ETL/ELT, data modeling, and data warehousing.

• Experience with SQL query optimization, Spark performance tuning, and CI/CD.

• Strong troubleshooting, problem-solving, and communication skills.

Preferred Qualifications

• Experience with Kafka, Kinesis, AWS Glue, or AWS Lambda.

• Familiarity with MongoDB and Terraform.

• Experience with Power BI or Tableau.