Senior Data Engineer

Headquartered in the USA, Tillster is the global leader in digital ordering and customer engagement solutions. For over a decade we have developed revolutionary self-service, ordering and payments solutions – for mobile, tablet, online, kiosk, call center, and more – creating personalized interactions based on consumer preferences, language, and currency. Our platform is compatible with 15+ unique POS systems, representing over 90% coverage in multi-unit restaurants.

We offer one platform: one scalable, enterprise class solution - to create world-class digital engagement solutions. Our mission and passion are one in the same:
Empower restaurants and consumers to engage and transact anywhere, anytime, and from any device - one consumer at a time, one order at a time, billions of times over. In doing so, together we are transforming e-commerce in restaurants and making the till grow for Tillster and our customers.

Are you a passionate data engineering with a knack for data?

The Data Science and Analytics team at Tillster is looking for a highly motivated Senior Data Engineer with strong problem-solving skills and hands-on experience building and maintaining real-time data pipelines. This role is primarily a data engineering position, with a meaningful secondary component supporting analytics and contributing to our dbt-based data modeling layer. You will pull data from multiple platforms, tools, and sources, elevating Tillster's data accessibility, analytical efficiency, and the quality of our data products.

• Own and maintain data warehouse infrastructure across Redshift, Big Query, 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 Mar Tech 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 Dev Ops 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.

• 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.

• 4+ years of experience developing in Python.
• 4+ years of experience in SQL (Redshift, Snowflake, Big Query).
• 2+ years working on AWS or equivalent cloud platform.
• 2+ years 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.

• 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 (dbt tests, schema tests) and CI/CD for data pipelines.
• Exposure to statistics, experimentation (A/B testing), or basic ML concepts.

• Salary hourly rate is $120,000k - $140,000k DOE
• Health Benefits: All full-time, regular employees and their dependents are eligible for medical, dental, vision and FSA benefits. Additional health benefits include Healthcare and Dependent Care…