Senior Data Engineer

Responsibilities: — Build and operate batch and incremental ingestion pipelines in Google Cloud to Smartly Data Platform. — Develop Airflow workflows using Python with best orchestration practices, including dag dependencies, retries, backfills, alerting, and recovery. — Build and maintain dbt transformations, from source-aligned staging models to curated warehouse datasets. — Add tests and documentation, and support version control and deployment checks. — Design practical storage patterns across Cloud Storage and BigQuery, considering formats, data grain, partitioning, clustering, retention, lifecycle, and access controls. — Improve data warehouse performance and cost through ongoing query and storage optimization. — Document data flows and operational practices so pipelines are understandable, supportable, and safe to extend. — Work with analytics, product engineering, and platform colleagues to clarify requirements and deliver dependable datasets. — Monitor freshness, completeness, volume, and schema changes so data problems are visible and addressed early. — Investigate pipeline failures and data discrepancies from source through downstream models, correct the root cause, and validate recovery. Requirements: — Professional experience on building data warehouses starting from data ingestion and landing to publishing data products. — Strong SQL and Python skills, with a track record of writing clear, maintainable code. — A solid understanding and hands on experience on data storage and warehouse design, including how structure, volume, access patterns, and retention affect reliability, performance, cost and data modelling. — Experience developing and supporting Airflow workflows or similar orchestration tool. — Practical dbt experience, including models, tests, documentation, and version-controlled deployment workflows. — Experience with solving production issues in data warehouse. — Clear written and spoken English, and the ability to work effectively with engineers and analysts. Useful Experience, but not required: — Google cloud development stack: Google Cloud Storage, BigQuery, Cloud SQL, PostgreSQL, or other Google Cloud data services. — Kafka or other event-streaming systems, and familiarity with Kubernetes. — Data lineage, cataloguing, observability, Tableau, or Redash. — Advertising, marketing, or product analytics data. Benefits: — At Smartly, we offer a place where you can do meaningful technical work while growing with a global team.