Strong hands-on experience with Snowflake, especially Data Metric Functions (DMFs)
Advanced experience with dbt (metadata, testing, orchestration)
Proven experience integrating observability tools like Splunk
Experience with incident management platforms (OpsGenie preferred)
Requirements:
Unified metadata collection and persistence: standardize dbt metadata capture, build a hardened dbt-to-Snowflake logging pipeline, and persist run_results.json and manifest.json into an Observability schema with automated cleanup and retention; apply observability rules at scale via Snowflake DMFs.
Data quality observability framework: implement and manage rules across validity, freshness, volume, schema values, and distribution; ensure monitoring for high-priority/Tier-1 tables.
DMF thresholding and performance optimization: design targeted Snowflake DMFs, define dynamic thresholds to reduce alert fatigue, and optimize DMF credit consumption to keep monitoring costs at 5–10% of total compute.
Observability alerting and incident management: build a Splunk-driven unified observability pane, create alerts correlating dbt failures with DMF violations, and integrate with OpsGenie for SLA tracking and auto-resolution; deliver executive dashboards.
Job description
Client: Workiva
Job Title: Senior Data Engineer – Data Observability (Snowflake, dbt, DMF)
Location: LATAM
Duration: 6months Role Overview We are looking for a highly skilled Senior Data Engineer with strong experience in Data Observability to help operationalize and scale a robust data reliability framework. This role will focus on implementing end-to-end observability across dbt, Snowflake Data Metric Functions (DMFs), Splunk, and OpsGenie, ensuring proactive detection and resolution of data quality issues across critical data assets. The mission is to establish a self-healing, highly visible data reliability layer that eliminates silent data failures and enables faster incident response.
