Staff Engineer

Roles and Responsibilities:

• Design, develop, operationalize robust and scalable data pipelines with automated data quality checks to support business needs and demonstrate ownership of live data pipelines and establish the patterns other engineers use to build theirs.
• Proficiency understanding and implementing data life cycles, data lineage, custom metadata, and data governance.
• Proficiency implementing BigQuery SQL procedures, functions, and similar, with actionable logging
• Optimize ETL processes and data workflows to ensure abiding by performance constraints, for efficiency and scalability.
• Together with the Principal Engineer and Architect, own the architecture of our data platform end to end ingestion through consumption across GCP, BigQuery, dbt, Airflow, and Python.
• Expertise in JSON, XML, text parsing using Dataflow, Python, or batch jobs.
• Define and enforce engineering standards across data teams: code review norms, testing strategy, reusable frameworks, CI/CD for data.
• Design, develop and maintain robust, and scalable data models and schemas to support analytics and reporting requirements.
• Optimize data processing performance, ensure high availability, scalability of data systems and solutions.
• Implement monitoring and alerting mechanisms to proactively identify and resolve issues.
• Ensure data quality and consistency through rigorous testing and validation processes in development and production tiers.
• Create, update, and maintain technical documentation of the data processes, pipelines, and models.
• Mentor and grow engineers across teams through design review, pair programming, and structured technical feedback.
• Partner directly with Engineering, Product, and business leadership to translate ambiguous business problems into technical requirements.
• Identify systemic problems no one has asked you to fix, and build the case for addressing them.
• Evaluate emerging technologies and lead the technical roadmap for the data platform, including a multi-quarter view of what we build next and what we retire.

Experience:

• 8+ years of experience in Data / ETL Engineering, as well as Data / ETL Architecture and pipeline development, including 3+ years operating at senior or lead level with demonstrated technical influence beyond your immediate team.
• 3+ years hands-on with the Google Cloud Platform (GCP), including deep BigQuery expertise: partitioning and clustering strategy, slot and reservation management, cost optimization at scale, and query performance tuning.
• Proven track record architecting, building and scaling cloud data platform serving multiple consuming teams — with specifics on scale, latency, and cost.
• Experience with the primary managed data services within GCP, including DataProc, Dataflow, BigQuery etc.
• Deep expertise in SQL, DBT, Python (Apache Airflow, Composer) and hands-on experience with ETL tools like Talend, Fivetran or similar.
• Demonstrated experience with streaming and near real-time architectures, including delivery semantics, schema evolution, and late-arriving data.
• Strong dimensional modeling expertise, and the judgment to know when to depart from it.
• Experience establishing data quality, observability, and testing frameworks that other engineers adopt and maintain.
• Experience with infrastructure as code and CI/CD for data workloads.
• Demonstrated ability to influence without authority — driving technical decisions across teams that don't report to you.
• Track record of mentoring engineers to promotion.
• Excellent written communication, including design documents that create alignment among senior stakeholders.