Take end-to-end ownership of the data platform's reliability, encompassing pipelines, warehousing, transformations, and observability
Design, build, and maintain robust data pipelines using Apache Airflow, orchestrating complex workflows across batch and near-real-time workloads
Manage and optimize the primary Snowflake data warehouse, handling schema design, clustering keys, materialized views, access controls, and strict cost governance
Build and maintain the dbt transformation layer, including model design, incremental strategies, dependency management, and documentation
Deploy and operate data platform services on Kubernetes (EKS), independently managing workloads, debugging pod issues, and tuning resource requests
Provision and manage data platform infrastructure, including Snowflake resources and Airflow, utilizing Terraform
Write high-quality SQL and Python for ETL tooling, pipeline logic, and data product delivery
Manage PostgreSQL as a source-of-truth operational database, focusing on query optimization, indexing, replication, and migrations
Lead the transition toward change data capture (CDC) for data ingestion, utilizing tools like Debezium to stream database changes
Implement comprehensive observability, SLA tracking, and alerting across the data platform using Datadog
Maintain CI/CD pipelines for DAG deployments, dbt runs, schema migrations, and container image builds
Collaborate with analytics, product, and full-stack development teams to model clean, well-documented data products
Navigate AWS environments (including RDS and S3) to manage data-adjacent services, read logs, and adjust scaling parameters