Data Engineer

About The Role The role owns the data infrastructure that powers analytics and product decisions - batch and streaming pipelines, warehouse modeling, and the orchestration layer that keeps data flowing reliably at scale. The engineer will work closely with analytics engineers, backend teams, and business stakeholders to turn raw, messy source data into trustworthy, well-modeled datasets that downstream teams can build on without hesitation. Key Responsibilities Design, build, and maintain ETL/ELT pipelines in Python and SQL, processing data from event streams, third-party APIs, and production databasesDevelop and optimize data models in Snowflake (or similar warehouse), including dimensional modeling, incremental loading strategies, and cost-conscious query tuningOrchestrate workflows using Airflow or Dagster, with robust scheduling, dependency management, failure alerting, and backfill proceduresImplement data quality frameworks - automated freshness tests, schema validation, and anomaly detection - to catch bad data before it reaches stakeholdersBuild and maintain streaming pipelines using Kafka, Kinesis, or Spark Structured Streaming for real-time use casesPartner with analytics engineers to maintain a clean, version-controlled dbt project with clear lineage and documentationContribute to platform decisions around tooling, infrastructure-as-code (Terraform), and CI/CD for data assets What We Are Looking For 3–6 years of data engineering experience building and operating production pipelines at scaleExpert-level SQL and strong Python; comfort debugging complex transformations and performance issuesHands-on experience with a modern data warehouse (Snowflake, BigQuery, or Redshift) and dbtProduction experience with an orchestrator such as Airflow, Dagster, or PrefectExperience with streaming or event-based architectures (Kafka, Kinesis, or equivalent)Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experienceBonus: experience with Terraform, AWS/GCP data services, data contracts, or building self-serve data platforms