Data Engineer: Build & Optimize Scalable ETL Data Pipelines

Ethereum Technologies; Alpharetta (GA); On-site; USD 110,000 - 160,000; Full time

Job summary

Ethereum Technologies in Alpharetta, GA is seeking an experienced Data Engineer to design, develop, and maintain scalable data pipelines and data processing solutions.

The ideal candidate will use Python, SQL, ETL/ELT, Spark, cloud platforms, and data warehousing to extract, transform, load data from multiple sources, monitor performance, and ensure data accuracy, quality, security, and reliability while collaborating with Data Scientists and Business Teams.

Qualifications

• Hands-on experience designing, developing and maintaining scalable data pipelines.
• Experience with ETL/ELT workflows and data processing architectures.
• Knowledge of Python, SQL and Spark for data transformation and analysis.
• Familiarity with cloud-based data platforms and data warehousing concepts.
• Ability to ensure data accuracy, quality, security and reliability.

Responsibilities

• Design, develop, and maintain scalable data pipelines.
• Build and optimize ETL/ELT workflows.
• Extract, transform, and load data from multiple sources.
• Develop data processing solutions using Python, SQL, and Spark.
• Implement data integration and transformation processes.
• Design and maintain data warehouses and data lakes.
• Work with cloud-based data engineering platforms.
• Monitor and troubleshoot data pipeline performance.
• Collaborate with Data Scientists, Analysts, and Business Teams.
• Optimize SQL queries and improve data processing performance.
• Follow Agile methodologies and participate in technical discussions.

Skills

Python

SQL

ETL/ELT

Cloud platforms

Data warehousing

Big Data technologies

Spark

Job description

Ethereum Technologies in Alpharetta, GA is seeking an experienced Data Engineer to design, develop, and maintain scalable data pipelines and data processing solutions.

The ideal candidate will use Python, SQL, ETL/ELT, Spark, cloud platforms, and data warehousing to extract, transform, load data from multiple sources, monitor performance, and ensure data accuracy, quality, security, and reliability while collaborating with Data Scientists and Business Teams.