● Own and maintain data warehouse infrastructure across Redshift, BigQuery, and Snowflake.
● Build and maintain real-time, batch, and streaming data pipelines that support analytics products and enable data-driven decisions across marketing, product, engineering, sales/account management, finance, and operations.
● Design data structures that deliver the right data, in the right format, to support real-time and near-real-time decision-making.
● Support the data needs of the MarTech stack, including Braze, Acoustic, MoEngage, and Segment.
● Modify and maintain SQL and Python ELT processes loading data into Redshift and other warehouses.
● Troubleshoot and maintain Airflow/Jenkins orchestration jobs; work with DevOps and cloud management on underlying infrastructure.
● Fulfill ad-hoc data extract requests and other data engineering duties as required.
● Provide ad-hoc SQL and analysis support to business stakeholders when requests fall outside the Data Analyst team’s current capacity.
● Maintain and update existing Looker Explores and dashboards to ensure consistent, accurate data as underlying warehouse structures change.
● Partner with Data Analysts to understand reporting requirements and ensure pipelines and derived tables serve their needs efficiently.
Architecture, dbt & Data Modeling
● Develop, test, and maintain dbt models to transform raw data into clean, analytics-ready datasets.
● Contribute to unifying GA4, CRM, and other data sources into a single consolidated warehouse structure.
● Build modular, reusable data models that support marketing funnels, segmentation, and campaign analytics.
● Implement basic automated data quality checks and validation rules within owned pipelines, and document data models and business logic for transparency.