Description:
We also love teaming up with app developers and businesses to foster growth and engagement through strategic partnerships. From co-marketing projects to solution provider programs and sponsorships, these collaborations are a big part of what makes Zapier shine.
Our awesome Ecosystem Data team is here to provide reliable data models and actionable insights so that everyone can make smart, informed decisions. As a Data Warehouse Engineer, you’ll be at the heart of shaping and scaling this vibrant ecosystem, helping us fulfill our mission of making automation available to everyone. Exciting times ahead!
About You
- You are experienced in Data Warehouse Engineering. You bring 4+ years of experience as a Data Warehouse Engineer, Data Engineer, Analytics Engineer, or in a similar role. You excel at self-organizing and managing projects end-to-end, from requirements gathering and solution design to implementation and delivery.
- You have strong proficiency in SQL and Python. You’re skilled at writing complex SQL queries for data transformation and analysis. You are also proficient in Python, capable of building Airflow functions and extracting data from third-party APIs.
- You have a deep understanding of data modeling concepts. You understand the nuances of when traditional data modeling approaches are effective and when they aren’t. You’ve designed data models and ETL pipelines with a focus on ease of use for end consumers, high performance, and scalability.
- You are committed to data quality. You prioritize data integrity and implement robust solutions for monitoring and ensuring data quality. You employ testing, monitoring, and alerting practices to maintain data reliability throughout the pipeline.
- You strive to align with business goals. You design data models that empower insightful analysis and reporting, always keeping the end goal in mind. You understand the key metrics and their implications, and you work closely with Data Science colleagues and cross-functional stakeholders to ensure your efforts align with broader objectives.
- You influence technical standards. You’re familiar with modern data platforms and best practices for scalability and performance. You contribute to shaping your team’s technical direction, including decisions on architecture, tooling, and strategies for technical improvements.
- You embrace progress over perfection. You understand that “perfect is the enemy of good” and take a pragmatic approach to shipping solutions. You prioritize delivering functional solutions quickly and iterating to refine and optimize them over time.
- You are a skilled written communicator. Zapier is a 100% remote team, and writing is our primary means of communication. You explain complex technical topics in a clear and approachable way
- You value collaboration and knowledge sharing. You work effectively with teammates at all technical levels. You take ownership of filling knowledge gaps about the data assets you manage and contribute to comprehensive documentation to elevate your peers with what you’ve learned.
- You are proactive and strategic. You proactively develop forward-thinking plans that prioritize stakeholder value and contribute to shaping the team’s technical direction. You stay curious about emerging technologies and stakeholder challenges, striving to connect the two in your work.
Things You’ll Do
- Design and Build Data Pipelines: Develop and maintain efficient data pipelines using Airflow, Databricks, and dbt to transform raw data into analytics-ready datasets for user-facing products and insights.
- Ensure Data Quality: Implement automated testing and monitoring systems to uphold data quality and integrity, leveraging best practices in observability and issue detection.
- Enable Self-Service Analytics: Partner with stakeholders across Zapier to understand their analytical needs and build data models and self-service analytics solutions using tools like Looker and Amplitude.
- Define Data Collection Strategies: Collaborate with product, marketing, and engineering teams to ensure products and services are properly instrumented to collect the right data for analytics.
- Shape Technical Direction: Contribute to architectural decisions, tooling choices, and strategies to optimize data storage, workflows, and schemas, ensuring scalability, accessibility, and security.
- Bridge Data to Insights: Work closely with Data Scientists and cross-functional stakeholders to bridge the gap between raw data and actionable insights, empowering teams to make informed, data-driven decisions.
- Mentor and Share Knowledge: Act as a resource for junior team members, offering guidance and knowledge-sharing to elevate team expertise and contribute to a culture of learning.