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Senior Data Engineer (Snowflake & Observability Implementation)SnapCode Inc • California, Maryland, United States
Postuler Maintenant
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Senior Data Engineer (Snowflake & Observability Implementation)

SnapCode Inc
  • US
    California, Maryland, United States
  • US
    California, Maryland, United States
Postuler Maintenant

À propos

Client: Workiva Location: LATAM Duration: 6 months
Job Title: Senior Data Engineer - Data Observability (Snowflake, dbt, DMF) 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.
Key Responsibilities
Unified Metadata Collection & Persistence
Standardize and automate dbt metadata capture across all model runs.
Build and maintain a hardened dbt-to-Snowflake logging pipeline to persist run_results.json and manifest.json into an Observability schema.
Implement automated cleanup and retention policies to manage storage efficiently.
Apply data observability rules at scale by pushing dbt checks into Snowflake DMFs.
Implement and manage observability rules across key dimensions:
Validity (data types, formats)
Freshness (timeliness, latency)
Volume (record count reconciliation)
Schema & Values (structural and value changes)
Distribution (anomaly detection, trend deviations)
Ensure data quality monitoring for high-priority and Tier-1 tables.
Design and implement targeted Snowflake DMFs instead of blanket monitoring.
Define dynamic thresholds (e.g., standard deviation-based) to reduce alert fatigue.
Analyze and optimize DMF credit consumption, keeping monitoring costs within 5-10% of total compute.
Build a single pane of glass for data observability using Splunk.
Create high-performance alerts correlating dbt job failures with DMF violations.
Ensure alerts include contextual payloads such as:
Failing dbt model or code link
Table owner
Downstream BI impact
Integrate Splunk alerts with OpsGenie for actionable incident management.
Configure:
Priority-based alert routing (Warning vs Critical)
Auto-resolution of alerts when issues self-heal
SLA tracking for MTTD (Mean Time to Detect) and MTTR (Mean Time to Resolve)
Build a Data Reliability Executive Dashboard (Splunk or Snowflake/Streamlit) to provide:
Overall Data Health Score
Volume and Freshness trends
Top offending models/tables
Month-over-month MTTD and MTTR improvements
Operational Standards & Documentation
Create detailed Runbooks / SOPs for on-call engineers.
Implement Monitoring-as-Code using version control (Terraform, dbt project files).
Maintain a weekly Observability Health Dashboard to identify noisy or unstable models.
Required Skills & Experience
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)
Strong SQL and data modeling skills
Experience building scalable, production‑grade data pipelines
Familiarity with cost optimization and performance tuning in Snowflake
Nice to Have
Experience with Streamlit dashboards
Infrastructure‑as‑Code (Terraform)
Background in data governance or data reliability engineering
Experience supporting on‑call or production data platforms
#J-18808-Ljbffr
  • California, Maryland, United States

Compétences linguistiques

  • English
Avis aux utilisateurs

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