Data Engineer

Akaasa Technologies; Atlanta (GA); On-site; USD 96,000 - 152,000; Part time

Job summary

Akaasa Technologies in Atlanta, GA is seeking a Data Engineer to design and maintain scalable data pipelines and cloud-based platforms. The role focuses on Python, SQL, Snowflake, DBT, and AWS Airflow, in a fast-paced, client-facing environment.

The ideal candidate has 5+ years of data engineering experience, strong data modeling, and hands-on work with ETL/ELT, cloud data platforms, and big data tools like Spark, Kafka, or Hadoop.

Qualifications

• 5+ years of experience in Data Engineering or Data Platform development.

Responsibilities

• Design, develop, and maintain scalable enterprise data pipelines and ETL/ELT workflows.

Skills

Python

SQL

Snowflake

DBT

AWS Airflow

ETL/ELT

Data Pipelines

Data Modeling

Cloud Data Platforms

AI/Automation

AWS Bedrock

Snowflake ML

Agile

Spark

Kafka

Hadoop

NoSQL

Kubernetes

Tools

AWS/Azure/GCP

Airflow

Job description

Data Engineer

Location: Atlanta, GA (100% Onsite)
Duration: 6 Months Contract
Interview: Virtual round

Technical Skills

Python | SQL | Snowflake | DBT | AWS Airflow | AWS | ETL/ELT | Data Engineering | Data Pipelines | Data Modeling | Spark | Kafka | Hadoop | NoSQL | Cloud Data Platforms | AI/Automation | AWS Bedrock | Snowflake ML | Agile

Note:

• Must be local with DL copy
• LinkedIn with location and photo (before 2023)

Position Overview

Our client is seeking a Data Engineer to support a key enterprise data engineering initiative focused on building and maintaining scalable data pipelines and cloud-based data platforms. The ideal candidate will have strong expertise in Python, SQL, Snowflake, DBT, and AWS Airflow, with the ability to work independently in a fast-paced, client-facing environment.

Required Skills & Experience

• 5+ years of experience in Data Engineering or Data Platform development.
• Strong hands-on expertise in:
  • Python (Must Have)
  • SQL (Must Have)
  • Snowflake
  • DBT
  • AWS Airflow
• Experience designing and supporting scalable ETL/ELT pipelines.
• Strong understanding of data modeling, relational databases, and cloud data platforms.
• Experience working with AWS, Azure, or GCP environments.
• Familiarity with big data technologies such as Spark, Kafka, or Hadoop.
• Experience with Agile development methodologies and cross-functional collaboration.
• Excellent analytical, troubleshooting, and communication skills.

Other Skills

• Exposure to AI/Automation technologies such as AWS Bedrock or Snowflake ML.
• Experience with real-time data processing and streaming analytics.
• Knowledge of machine learning pipelines and data science workflows.
• Experience with Kubernetes, Apache NiFi, or similar orchestration tools.
• Cloud certifications (AWS, Azure, or GCP) are a plus.
  

Key Responsibilities

• Design, develop, and maintain scalable enterprise data pipelines and ETL/ELT workflows.
• Build and optimize cloud-based data platforms to support analytics and business intelligence.
• Develop data transformation solutions using DBT, Snowflake, Python, and SQL.
• Collaborate with business stakeholders, analysts, and data scientists to deliver high-quality data solutions.
• Implement best practices for data governance, security, and compliance.
• Monitor, troubleshoot, and optimize data pipeline performance and reliability.
• Support workflow orchestration using AWS Airflow and modern cloud technologies.
• Contribute to data platform modernization and automation initiatives.