Role Overview
We need a senior Data Engineer with eight or more years of experience building and operating data pipelines, warehouses, and analytics foundations. You will make data reliable, observable, and ready for product analytics, reporting, and ML-adjacent workloads.
What You Will Do
- Design and implement batch and streaming ETL/ELT pipelines with orchestration best practices.
- Model and optimize warehouse schemas (star/snowflake, SCD strategies as needed).
- Ensure data quality: validation, monitoring, lineage awareness, and incident playbooks.
- Partner with software engineers on event capture, APIs, and operational data contracts.
- Support analytics and stakeholders with performant datasets and clear documentation.
Must-Have Skills
- 8+ years in data engineering or equivalent senior data platform roles.
- Strong SQL and experience with major warehouses (Snowflake, BigQuery, Redshift, or Databricks).
- Pipeline tools (Airflow, Dagster, dbt, or similar) and workflow reliability patterns.
- Python or Scala for data jobs; version control and CI for data code.
- Cloud data stacks on AWS, GCP, and Azure with cost/performance trade-off analysis.
- DevOps tooling for data platforms using Docker, Kubernetes, and Jenkins.
Nice to Have
- Streaming (Kafka, Flink, Spark Streaming) in production.
- Data governance, PII handling, and access control patterns.
- Exposure to feature stores or ML feature pipelines (not required to train models).