Senior Marketing Data Ops Engineer — Campaign Pipelines

GEICO; Indianapolis (IN); On-site; USD 115,000 - 260,000; Full time

Job summary

GEICO is seeking a hands-on data/software engineer to build instrumentation and event pipelines powering campaign and journey triggers. You’ll collaborate with CRM/marketing teams to ensure reliable audience data across multiple sources.

You’ll leverage Python/SQL in a cloud environment (Azure, AWS, or GCP) and implement ETL/ELT pipelines with data quality monitoring. Strong REST API integration and data warehousing experience are essential.

Qualifications

• 7+ years building data tools/pipelines in Python, Scala, or similar languages.
• 7+ years working in SQL against enterprise data warehouses (Snowflake, Databricks, or similar).
• 5+ years building ETL/ELT pipelines (batch or streaming) from files, databases, and APIs.
• 5+ years working with cloud infrastructure (Azure, AWS, or GCP) and DevOps practices.
• Comfort integrating systems via REST APIs.
• BA/BS in Computer Science, Information Technology, Mathematics, Engineering, or related field.

Responsibilities

• Build instrumentation and event pipelines that generate audience/trigger data for CRM and marketing automation platforms where it doesn’t already exist.
• Batch and streaming ETL/ELT pipelines connecting campaign, CRM, and customer data across multiple sources.
• REST API integrations between internal data systems and CRM/marketing automation platforms.
• Data quality checks and monitoring to keep campaign-critical pipelines reliable at scale.

Skills

Python

SQL

ETL/ELT pipelines

Cloud infrastructure

REST APIs

Education

BA/BS in Computer Science or related field

Tools

Snowflake

Databricks

Azure

AWS

GCP

Job description

GEICO is seeking a hands-on data/software engineer to build instrumentation and event pipelines powering campaign and journey triggers. You’ll collaborate with CRM/marketing teams to ensure reliable audience data across multiple sources.

You’ll leverage Python/SQL in a cloud environment (Azure, AWS, or GCP) and implement ETL/ELT pipelines with data quality monitoring. Strong REST API integration and data warehousing experience are essential.