Senior Product Manager overseeing data platform and intelligence capabilities at Wattpad. Collaborating with cross - functional teams to build systems for smarter product decisions.
About the role
- Senior Data Engineer for a membership-based veterinary care company, leading data pipelines and mentoring team members. Designing ETL workflows and collaborating with data scientists and engineers.
Responsibilities
- Own the design, development, and reliability of production data pipelines using Python, SQL, and modern orchestration tools
- Architect and implement ETL/ELT workflows to move data between source systems, data warehouses, and downstream consumers at scale
- Lead the development and optimization of data pipelines that feed machine learning models, including feature engineering, training data preparation, and inference pipelines
- Design and maintain ingestion and chunking pipelines for RAG systems, including document parsing, embedding generation, and vector store population
- Mentor and guide a more junior data engineer: conduct code reviews, pair on complex problems, and foster their technical growth
- Organize and prioritize data engineering tasks, ensuring the team delivers reliably against business timelines and technical standards
- Collaborate with data scientists, ML engineers, and product teams to productionize models and ensure reliable, performant data delivery
- Design and implement monitoring, alerting, and data quality frameworks to proactively catch pipeline failures and data drift
- Drive the design and evolution of our data warehouse and data lake architecture, making strategic decisions about tooling, partitioning, and performance
- Work with stakeholders across the business to understand data needs and translate them into scalable, well-documented data solutions
- Champion engineering best practices: documentation, testing, CI/CD, and knowledge sharing within the team
Requirements
- 5+ years of relevant experience as a Data Engineer or in a similar data-focused role. Experience in startups and fast-paced environments strongly preferred. A Bachelor’s degree in Computer Science, Data Science, Engineering, or a related field is required; a Master’s degree is a plus.
- Strong proficiency in Python and SQL for data manipulation, pipeline development, and scripting at scale
- Deep experience with at least one orchestration framework (e.g., Airflow, Dagster, Prefect) for scheduling and managing complex data workflows
- Solid experience with cloud platforms (AWS preferred) and their data services (e.g., S3, RDS, Redshift, Lambda, Glue)
- Hands-on experience with ML pipeline concepts: feature stores, model training data preparation, batch/streaming inference pipelines
- Working knowledge of RAG pipeline components: document loaders, text chunking strategies, embedding models, and vector databases (e.g., Pinecone, Weaviate, pgvector, Chroma)
- Strong experience with Snowflake and data warehousing tools (e.g., dbt, BigQuery). Experience with data lake architectures is a plus.
- Proficiency with AI-assisted engineering practices, including the use of agentic coding tools (e.g., Claude Code, GitHub Copilot, Cursor) to accelerate development workflows, code generation, and debugging
- Deep understanding of data modeling, schema design, and data quality frameworks
- Demonstrated ability to mentor junior engineers, lead technical discussions, and influence technical direction without formal authority
- Strong organizational skills with a track record of prioritizing competing workstreams and delivering projects on time
- Experience with version control (Git), CI/CD pipelines, and infrastructure-as-code practices.
Benefits
- Competitive salary
- Equity ownership
- Health, dental + vision insurance
- Upward mobility and growth opportunities
- Generous paid-time off, parental leave, and company wide holidays
- Discounted veterinary care for your loved ones
- Growth opportunities
- An opportunity to make a real impact on the people around you
- A collaborative group of people who live our core values and have your back
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