Staff Data Engineer

What you'll do

• Architect, design, lead, and build an end-to-end, performant, reliable, scalable data platform.
• Work as an independent contributor: solve problems and deliver high-quality solutions with minimal oversight and strong ownership.
• Mentor and guide junior engineers to deliver complex, next-generation features.
• Bring a customer-centric, product-oriented mindset. Collaborate with customers and internal stakeholders to resolve product ambiguities and ship features that solve real customer problems.
• Partner with engineering, product, design, and other stakeholders to design and architect new features.
• Experimentation mindset: autonomy and empowerment to validate a customer need, get team buy-in, and ship a rapid MVP.
• Quality mindset: you treat quality as a non-negotiable part of your software deliverables.
• Analytical mindset: instrument and deploy new product experiments with a data-driven approach.
• Monitor, triage, and resolve production issues for the team's services.
• Create and maintain data pipelines and foundational datasets to support product and business needs.

What you bring

Required Experience

• 10+ years designing, implementing, and delivering highly scalable, performant data platforms.
• Experience building large-scale data processing pipelines using ETL/ELT, batch, and stream processing.
• Expert-level proficiency in PySpark, Python, and SQL.
• Expertise in data modeling, relational databases, and NoSQL data stores (e.g., MongoDB).
• Experience with big data technologies such as Kafka, Spark, Iceberg, data lakes, and the AWS stack (EKS, EMR, Serverless, Glue, Athena, S3, etc.).
• Knowledge of security best practices and data privacy concerns.
• Strong problem-solving skills and attention to detail.

Nice to have

• Experience or knowledge of data processing platforms such as Databricks or Snowflake.