Data Engineer II: Build Scalable Pipelines & Data Lakes

ICW Group; San Diego (CA); On-site; USD 95,000 - 161,000; Full time

Benefits offered by this job

Competitive benefits package

Paid time off

401K retirement plan with companymatch

Job summary

ICW Group is seeking a Data Engineer II who will design, develop, and implement data pipelines and storage solutions, partnering with IT Managers, BI, and Data Governance teams. You will help solve data problems, enable data-driven decisions, and optimize data delivery architecture across projects.

The role emphasizes building reliable, scalable pipelines, data quality, and collaboration with multiple teams to drive the data platform forward in a dynamic environment.

Qualifications

• Bachelor's degree in Computer Science, Applied Mathematics, Engineering, or related field.
• Minimum 3 years of experience in data integration/engineering (Cloud/Traditional).
• Insurance industry experience is a plus.
• Strong knowledge of data governance and data quality practices.

Responsibilities

• Design, develop, and maintain scalable data pipelines (batch/streaming).
• Analyze data elements and build conceptual/logical/physical data models.
• Design and support data warehouse schemas and ETL/ELT mappings.
• Test data sources, optimize performance, and reduce costs.
• Collaborate with BI/Data Science teams and data architects to ensure data availability and quality.

Skills

Data pipelines

ETL/ELT mappings

Data modeling

SQL

Python

Spark

Kafka

Hadoop

Databricks

Snowflake

Redshift

AWS

Education

Bachelor's degree in Computer Science or related field

Tools

MS-SQL

PostgreSQL

SSIS

Informatica

Talend

AWS

Job description

ICW Group is seeking a Data Engineer II who will design, develop, and implement data pipelines and storage solutions, partnering with IT Managers, BI, and Data Governance teams. You will help solve data problems, enable data-driven decisions, and optimize data delivery architecture across projects.

The role emphasizes building reliable, scalable pipelines, data quality, and collaboration with multiple teams to drive the data platform forward in a dynamic environment.