Analytics Engineer — Mobile Marketing Data Pipelines

Activision Publishing Inc. in; Santa Monica (CA); On-site; USD 79,000 - 147,000; Full time

Benefits offered by this job

Medical, dental, vision

401(k) with company match

Paid holidays and vacation

Relocation assistance

Job summary

Activision is seeking an Analytics Engineer to support mobile marketing analytics operations and the data systems that power marketing measurement, attribution, and reporting. The role combines production analytics with analytics engineering development to maintain existing data systems and build new data solutions.

Responsibilities include owning data pipelines, resolving data quality issues, and designing datasets using SQL and Python, while collaborating with analytics, engineering, and

Qualifications

• 2+ years of experience in analytics engineering, data engineering, or related data-focused role.
• Experience designing, implementing, and maintaining production data pipelines.
• Strong SQL and Python for data analysis, transformation, and troubleshooting.
• Experience with workflow orchestration platforms (Airflow, Dagster, Prefect, etc.).

Responsibilities

• Own the operation and reliability of marketing analytics data pipelines and data products.
• Investigate data quality issues, pipeline failures, and reporting discrepancies.
• Design and maintain data pipelines, transformations, and analytics datasets using SQL and Python.
• Collaborate with analytics, engineering, and business stakeholders to deliver effective data solutions.

Skills

SQL

Python

Communication skills

Problem solving

Team collaboration

Tools

Airflow

Dagster

Prefect

Azure Data Factory

dbt

Airbyte

Databricks

Git

GitHub

Job description

Activision is seeking an Analytics Engineer to support mobile marketing analytics operations and the data systems that power marketing measurement, attribution, and reporting. The role combines production analytics with analytics engineering development to maintain existing data systems and build new data solutions.

Responsibilities include owning data pipelines, resolving data quality issues, and designing datasets using SQL and Python, while collaborating with analytics, engineering, and