Senior Data Engineer

Tillster • Portland, OR

2d • $130,000 - $150,000

About The Position

Tillster’s Data Science and Analytics team is seeking a highly motivated Senior Data Engineer with strong problem-solving skills and hands-on experience building and maintaining real-time data pipelines. The role is primarily focused on data engineering, with a secondary component supporting analytics and Tillster’s dbt-based data modeling layer. The engineer will bring together data from multiple platforms, tools, and sources to improve data accessibility, analytical efficiency, and the quality of data products.

The position owns and maintains warehouse infrastructure across Redshift, BigQuery, and Snowflake; builds real-time, batch, and streaming pipelines; and supports data-driven decisions across marketing, product, engineering, sales/account management, finance, and operations. It also supports the MarTech stack, modifies SQL and Python ELT processes, troubleshoots orchestration jobs, and fulfills ad-hoc data requests.

The role provides SQL and analysis support to business stakeholders, maintains Looker Explores and dashboards, and partners with Data Analysts to ensure pipelines and derived tables meet reporting needs. It also develops and maintains dbt models, contributes to consolidating GA4, CRM, and other sources into a unified warehouse structure, builds reusable models for marketing analytics, and implements basic data quality checks and documentation.

Tillster is a global provider of digital ordering and customer engagement solutions for restaurants. The company describes itself as a growth-phase, venture-funded organization focused on empowering restaurants and consumers and fostering an inclusive, diverse work environment. No visa sponsorship is offered.

Requirements

• At least 4 years of experience developing in Python.
• At least 4 years of experience with SQL and data warehouses such as Redshift, Snowflake, or BigQuery.
• At least 2 years of experience working on AWS or an equivalent cloud platform.
• At least 2 years of experience working with Airflow or comparable orchestration tools.
• Working knowledge of dbt for data transformation and modeling.
• Hands-on experience supporting the data needs of BI tools such as Looker or Tableau.
• Experience with real-time ingestion tools such as Snowpipe, Stitch, Fivetran, or Kinesis.
• Experience working in an Agile development environment.

Nice To Haves

• Experience with Segment, Braze, Acoustic, or MoEngage data integrations.
• Familiarity with LookML and Looker semantic layer concepts.
• Experience with Google Analytics (GA4) as a data source.
• Knowledge of data quality frameworks, including dbt tests or schema tests, and CI/CD for data pipelines.
• Exposure to statistics, experimentation such as A/B testing, or basic machine-learning concepts.

Responsibilities

• Own and maintain data warehouse infrastructure across Redshift, BigQuery, and Snowflake.
• Build and maintain real-time, batch, and streaming data pipelines supporting analytics products and decisions across marketing, product, engineering, sales/account management, finance, and operations.
• Design data structures that provide data in suitable formats for real-time and near-real-time decision-making.
• Support data needs for 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, collaborating with DevOps and cloud management on underlying infrastructure.
• Fulfill ad-hoc data extract requests and perform other data engineering duties as required.
• Provide ad-hoc SQL and analysis support to business stakeholders when requests exceed the Data Analyst team’s current capacity.
• Maintain and update Looker Explores and dashboards to ensure data remains consistent and accurate as warehouse structures change.
• Partner with Data Analysts to understand reporting requirements and ensure pipelines and derived tables serve those needs efficiently.
• Develop, test, and maintain dbt models that transform raw data into clean, analytics-ready datasets.
• Contribute to unifying GA4, CRM, and other data sources into a consolidated warehouse structure.
• Build modular, reusable data models for marketing funnels, segmentation, and campaign analytics.
• Implement basic automated data quality checks and validation rules within owned pipelines.
• Document data models and business logic for transparency.

Benefits

• Medical, dental, vision, and flexible spending account (FSA) benefits for eligible full-time regular employees and their dependents.
• Healthcare and Dependent Care reimbursement programs.
• Employee Assistance Program (EAP) and Optum Care 24-hour confidential medical counseling services.
• Ten paid holidays per calendar year.
• Paid time off: eligible full-time regular employees earn 15 days in their first 12 months of continuous service and 22 days in subsequent years; eligible part-time employees earn prorated PTO.
• Eligibility to participate in the 401(k) plan beginning on the employment start date.
• College tuition and education assistance programs.
• Udemy Learning courses and ongoing learning and development opportunities.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed