BigQuery, Redshift, Synapse, Databricks) Implement data quality, testing, monitoring and observability across pipelines and models Build streaming pipelines where the use case warrants it (Kafka, Kinesis, Pub/Sub, Flink) Partner with analysts, scientists, BI developers and ML engineers to deliver the data products they need Contribute to data … Vault or domain-driven approaches CI/CD for data pipelines, version control discipline, infrastructure-as-code basics (Terraform) Streaming and big data exposure (Kafka, Kinesis, Spark, Flink) is a plus Data quality and observability tooling (Great Expectations, Monte Carlo, Soda, dbt tests) is a plus Engineering & Soft Skills ...