Data Engineer II: BI Dashboards & Data Pipelines (Hybrid)

Early Warning Services LLC; Chicago (IL); Hybrid; USD 83,000 - 110,000; Full time

Benefits offered by this job

Healthcare Coverage

401(k) Retirement Plan

Paid Time Off

Paid Parental Leave

Maven Family Planning

Job summary

Early Warning Services LLC is seeking a Data Engineer to design, develop, and maintain BI solutions across multiple tech stacks. You will translate metrics into actionable insights, build datamarts, and craft comprehensive dashboards to inform planning and performance across the organization.

The role requires 2–4 years of data engineering experience with PySpark/Python in a Linux environment, strong Tableau skills, and a track record of building scalable data pipelines in enterprise settings.

Qualifications

• Bachelor’s degree in a related field.
• 2–4 years of data engineering experience with PySpark/Python in a Linux environment.
• Experience with Tableau Server and dashboards.
• Strong problem solving, testing, and analytical skills.
• Knowledge of ETL, data modeling, and data warehousing.
• Experience with SQL, Spark, Hadoop or AWS/S3.
• Experience collaborating with enterprise teams in regulated environments.
• Strong communication skills.
• Background and drug screen.

Responsibilities

• Define requirements for reports and dashboards with business users.
• Design and develop backend data sources using Cloudera stack.
• Create complex Tableau dashboards, scorecards, and reports.
• Perform in-depth data analysis and cause-effect studies.
• Design ETL processes to support analyses.
• Guide data platforms and standards.
• Mentor interns and support Data Scientists.
• Collaborate with EW teams on data platform enhancements.

Skills

PySpark

Python

Spark

Scala

Tableau

SQL

ETL

Data Modeling

Hadoop

AWS S3

Education

Bachelor's degree

Tools

Tableau

Cloudera

Hive

Impala

Linux

Job description

Early Warning Services LLC is seeking a Data Engineer to design, develop, and maintain BI solutions across multiple tech stacks. You will translate metrics into actionable insights, build datamarts, and craft comprehensive dashboards to inform planning and performance across the organization.

The role requires 2–4 years of data engineering experience with PySpark/Python in a Linux environment, strong Tableau skills, and a track record of building scalable data pipelines in enterprise settings.