Senior Software Engineer

Who you are

• 6+ years of data engineering experience with strong Python and SQL skills, including designing and operating scalable batch and/or streaming data pipelines and orchestration (e.g., Dagster, Airflow, Luigi, dbt, Snowflake, Spark, Kafka, Databricks, or similar technologies)
• Experience working with cloud-based application development and data platforms, including AWS services and modern data warehouses (e.g., Snowflake)
• Experience evaluating different data platform integration tooling (e.g. APIs, CDC, batch ingestion, streaming) and collaboration/integration tools like GitHub, Argo, Jenkins, or equivalent
• Experience designing and implementing robust data models and transformations in the data warehouse (e.g., dbt, Snowflake) as well as self-service tooling for the other members of the data platform team
• Ability to articulate technical concepts to mixed technical and non-technical audiences, collaborate across teams, mentor less experienced engineers, and maintain clarity in ambiguous problem spaces
• Demonstrates curiosity about technology, a bias toward continuous learning, and a strong sense of ownership over architecture, quality, and process improvements in a fast-moving environment

What the job involves

• As a Senior Software Engineer, Data, you will design, build, and operate the next generation of our data platform and products – going beyond ID to power a networked digital identity – while keeping member privacy, security, and reliability at the core
• Build and operate scalable, reliable data systems and pipelines – from ingestion to modeling to visualization – so Analysts and Engineers can self-service changes in an automated, tested, secure, and high-quality manner
• Develop and maintain end-to-end data products and pipelines (batch and/or streaming) that collect, clean, transform, and model data, and own the infrastructure that powers them to unlock new business use cases and reporting
• Implement and maintain infrastructure-as-code, CI/CD, and shared developer tooling for data products (e.g., Pulumi/Terraform, GitHub, orchestration tools like Dagster/Airflow) to make it easy and safe for teams to build, test, and ship changes across environments
• Improve the security, compliance, and cost posture of the data stack through robust dependency management, IAM and secrets hardening, observability, and performance/cost optimizations
• Partner with product and other stakeholders to uncover requirements, make architectural decisions, and continuously improve the data platform and processes