Senior Data Engineer (Snowflake & Observability Implementation)SnapCode Inc • United States
Senior Data Engineer (Snowflake & Observability Implementation)
SnapCode Inc
- United States
- United States
About
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.
Key Responsibilities
1. 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 .
2. Data Quality & Observability Framework
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.
3. DMF Thresholding & Performance Optimization
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.
4. Observability & Alerting (Splunk Integration)
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
5. Incident Management & SLA Enforcement (OpsGenie)
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)
6. Reporting & Executive Visibility
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
Languages
- English
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