ETL & Informatica Developer: Data Pipelines & Big Data

Ethereum Technologies LLC; Dallas (TX); On-site; USD 90,000 - 130,000; Full time

Job summary

ETHEREUM TECHNOLOGIES LLC seeks a data engineering professional to design databases, build ETL pipelines, and develop scalable data processes. You will analyze data needs, create and optimize data architectures, and implement automated solutions to improve data handling efficiency.

Your work includes validating models, exploring new data sources, and collaborating with teams to operationalize analytics. This role emphasizes scalable data infrastructure and adherence to data standards.

Responsibilities

• Conducts logical and physical database design
• Identifies unique opportunities to collect new data.
• Designs ETL processes and data pipelines to build large, complex data sets.
• Strategizes new uses for data and its interaction with data design.
• Finds new uses for existing data sources.
• Conducts statistical modeling and experiment design.
• Tests and validates predictive models.
• Implements automated processes for efficiently producing scale models.
• Designs, modifies and builds new data processes.
• Implement, configure, administer, monitor Hadoop clusters
• Implements new or enhanced software designed to access and handle data more efficiently.
• Prepare and communicate status, issues, and opportunities to the business.
• Provides technical assistance to junior team members
• Create, refine and enforce data management standards, policies, and procedures.
• Evaluates emerging Big Data technologies to develops next-generation Big Data analytics framework

Skills

Database design

ETL development

Data pipelines

Statistical modeling

Experiment design

Predictive modeling

Data governance

Big data concepts

Tools

Hadoop

SQL

Python

Spark

Job description

ETHEREUM TECHNOLOGIES LLC seeks a data engineering professional to design databases, build ETL pipelines, and develop scalable data processes. You will analyze data needs, create and optimize data architectures, and implement automated solutions to improve data handling efficiency.

Your work includes validating models, exploring new data sources, and collaborating with teams to operationalize analytics. This role emphasizes scalable data infrastructure and adherence to data standards.