SENIOR DATA ENGINEERSENIOR DATA ENGINEERThe 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.
Data Engineering• 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.
Data Analysis• 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.
Requirements• 4+ years of experience developing in Python.
• 4+ years of experience in SQL (Redshift, Snowflake, BigQuery).
• 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.
Nice to Have• 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.
Pay and Benefits (USA)- Salary hourly rate is $130,000k - $150,000k 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 reimbursement programs, Employee Assistance Program ("EAP") and Optum Care 24-hour confidential medical counseling services.
- Holidays: The company observes ten (10) paid holidays per calendar year.
- Paid Time Off (PTO): Full-time, regular employees earn 15 days of PTO in the first 12-months of continuous service, and 22 days in subsequent years. Eligible part-time employees earn pro-rated PTO.
- Retirement: Effective with your employment start date, you will be eligible to participate in the 401(k) Plan.
- Education, Learning & Development: We offer college tuition and education assistance programs; Udemy Learning courses; and ongoing learning and development opportunities.
The Interview Process- Recruiter interview with a Talent Acquisition Specialist
- Interview with the Data Science Team
- Data Challenge/Take Home Challenge
- Final interview with our Data Science Team Leader
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