Remote Data Engineer: AWS Pipelines & Analytics

Ethereum Technologies LLC; Harrisburg (Dauphin County); Remote; USD 105,000 - 141,000; Full time

Job summary

Ethereum Technologies in Harrisburg, PA is seeking an experienced Data Engineer to design scalable data pipelines, build AWS-based data solutions, and deliver analytics to support research and decision-making.

The role emphasizes collaboration with data scientists and analysts, data governance, and data quality practices, with a strong focus on ETL, cloud services, and modern data platforms.

Qualifications

• 5+ years of hands-on AWS cloud data services experience.
• 5+ years of programming with Python, R, Java, Scala, or C++.
• 5+ years of SQL and relational/NoSQL databases experience.
• 5+ years of experience with Git, CI/CD, and data modeling.

Responsibilities

• Design, develop, and optimize scalable data pipelines and ETL processes.
• Build cloud-based data solutions using AWS services (S3, Glue, Redshift, EMR, Athena, Lambda).
• Develop data workflows using Airflow, AWS Step Functions, or similar tools.
• Integrate, transform, and analyze large datasets using SQL and Python.
• Develop dashboards, reports, and analytical models.
• Implement data quality, governance, monitoring, and validation frameworks.
• Collaborate with data scientists, analysts, and stakeholders.
• Support data migration, modernization, and system integration initiatives.

Skills

Python

SQL

Data modeling

CI/CD

Git

Data governance

Data quality

REST APIs

Analytical thinking

Communication

Tools

AWS

Airflow

Spark

Hadoop

Kafka

Informatica

MuleSoft

Talend

TIBCO

Git

CI/CD pipelines

Job description

Ethereum Technologies in Harrisburg, PA is seeking an experienced Data Engineer to design scalable data pipelines, build AWS-based data solutions, and deliver analytics to support research and decision-making.

The role emphasizes collaboration with data scientists and analysts, data governance, and data quality practices, with a strong focus on ETL, cloud services, and modern data platforms.