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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer - **Company:** TaskRabbit - **Location:** San Francisco, CA, United States - **Experience:** Expert - **Salary:** $130,000.0 - $170,000.0 - **Contract:** Permanent contract - **Skills:** Sql Data Warehouse, Java (Programming Language), Artificial Intelligence, Airflow, BigQuery, Code Review, Information Engineering, Cursor (Graphical User Interface Elements), Dimensional Modeling, Python (Programming Language), Machine Learning, Standard Sql, Tableau (Software), GitHub Copilot, Snowflake, Apache Kafka, Virtual Agents, Stream Processing, Looker Analytics, Data Pipelines - **Published:** August 23, 2026 - **Apply:** https://www.dice.com/job-detail/c184b4aa-241f-47f2-aeb4-22003bf7bf47 ## About the Role * Experience building and maintaining ELT data pipelines using modern tools such as dbt, Airflow, and Fivetran * Experience with a cloud data warehouse such as Snowflake, BigQuery, or Redshift * Solid data modeling skills (e.g., dimensional modeling, star/snowflake schemas) * Proficient in SQL and at least one general-purpose programming language (e.g., Python, Java, or Scala) * Regularly use AI coding assistants (e.g., Copilot, Cursor, Claude Code) in your day-to-day work, and know how to prompt, review, and validate AI-generated code rather than just accept it * Comfortable with ambiguity - this is a discovery-stage team proving out new bets, not a mature, fully-scoped platform * Familiarity with BI or semantic-layer tools such as Looker, Mode, or Tableau * Experience with streaming platforms such as Kafka or Kinesis - this team's predictions run on event-driven triggers (weather events, life events), so comfort with real-time data processing is a strong plus. ## Description We're hiring a Senior Data Engineer to build the data foundation for a new discovery-stage team focused on Taskrabbit client retention and personalization. The team's mandate is to turn our biggest unaddressed retention bet - predicting what home service a client will need and when, then reaching them proactively - from concept into validated, in-market tests. You'll be one of four new hires on a small, cross-functional pod (Product, Design, Marketing, BizOps, Machine Learning, and Engineering) reporting through Product and matrixed with Data Engineering leadership. This is a hands-on, individual-contributor role one level below our Staff Data Engineer track: you'll own the design and build of specific data pipelines and models rather than set architectural direction for the broader platform, working closely with the team's Solutions Architect and Machine Learning Engineer as you go. It's a strong fit for someone who wants outsized ownership on a small team, is energized by ambiguity and fast iteration, and wants to help prove out (or kill) a major product bet with real evidence rather than another deck. The ideal candidate has solid experience with modern data tools - dbt, Airflow, Snowflake (or equivalent) - and is genuinely excited to work with AI coding tools day to day. We want someone who already leverages AI (e.g., GitHub Copilot, Cursor, Claude Code) to write, test, and review code faster, and who can use that speed to move a discovery team from idea to shipped test quickly, not someone who treats AI assistance as optional or occasional. What you will work on * Build and maintain the data pipelines and models that capture client home profiles, job history, and seasonal or event-driven signals (weather, life events, moves) feeding a predictive personalization engine * Partner with the team's Machine Learning Engineer and Solutions Architect to get data model-ready for predictions about what service a client will need and when * Build the pipelines that connect personalization signals into CRM and marketing channels (email, SMS, push, onsite) so predictions show up consistently across the client experience * Develop dbt models and semantic layers that let the team quickly stand up and measure in-market tests, such as multi-category punch cards or a recurring-category revenue model * Use AI coding tools as a default part of your workflow - to scaffold pipelines, write tests, and speed up code review - so the team can move from hypothesis to live test quickly * Contribute to the technical documentation and roadmap that will inform how this data foundation scales if the team's bets prove out * Work daily with Product, Design, Marketing, BizOps, and ML partners in a small, fast-moving pod ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) - [How Cisco embraced a DevOps culture within its network engineering team](https://www.wearedevelopers.com/videos/99-how-cisco-embraced-a-devops-culture-within-its-network-engineering-team) - [Hacking AI at the Edge of the Indian Ocean](https://www.wearedevelopers.com/videos/100177-hacking-ai-at-the-edge-of-the-indian-ocean) - [Data Governance in the Era of AI](https://www.wearedevelopers.com/videos/1622-data-governance-in-the-era-of-ai) ## Related Articles - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Dev Digest 132 - Binging WADFlix?](https://www.wearedevelopers.com/magazine/473-dev-digest-132-binging-wadflix)