Software Engineer Data

As a Software Engineer II - Data, your role involves contributing to the design and development of data systems, including pipelines, APIs, analytics, AI, and machine learning at scale. You will be a key member of the Data Products team, responsible for building and maintaining production-grade pipelines and platform components that drive business and product outcomes. Your focus will be on writing high-quality, scalable, and maintainable code across data pipelines, APIs, and data platform services. Key Responsibilities: - Write high-quality, scalable, and maintainable code across data pipelines, APIs, and data platform services. - Collaborate with senior engineers, analysts, and product stakeholders to translate technical requirements into working solutions. - Develop and support APIs, batch and real-time data flows, ensuring reliability and performance in 24x7 environments. - Contribute to data modeling, transformation logic, and system design decisions to support reporting, analytics, and data delivery needs. - Participate in the end-to-end software development lifecycle, including planning, testing, deployment, and operations. - Take ownership of features and components, seeing them through from design to deployment. - Document technical decisions, workflows, and runbooks to support long-term maintainability and clarity for peers. - Practice responsible data governance, ensuring data quality, privacy, and lineage are considered in all development. - Continuously learn and grow through code reviews, pairing, and technical mentorship. Qualifications Required: - 2+ years of development experience, with production systems in cloud environments. - Proficiency in Python and/or Golang, and SQL for data processing, transformation, and orchestration tasks. - Experience with at least one modern cloud platform (e.g., GCP, AWS, or Azure). - Experience developing REST or GraphQL APIs and internal data access layers. - Experience building and maintaining ETL/ELT pipelines or API-driven data services. - Experience with source control (e.g., Git), automated testing, and CI/CD practices. - Exposure to orchestration tooling such as n8n, Cloud scheduler, Airflow, Step Functions, or similar. - Understanding of data modeling concepts and cloud warehousing (e.g. Databricks, BigQuery, Snowflake or other). - Familiarity with Kafka, Pub/Sub, or other event-based systems. - Awareness of data quality, observability, and governance principles in engineering contexts. - Strong written and verbal communication skills, with an ability to share context with both technical peers and cross-functional partners. - Experience working with containerized environments (e.g., Docker, Kubernetes). - Exposure to infrastructure-as-code, especially for deploying and managing data workflows. - Hands-on use of BI tools like Looker or Tableau. In this role, your success will depend on your proactive and collaborative problem-solving approach, ability to manage multiple priorities, commitment to high technical standards, and willingness to learn and grow continuously.,