Data Quality / Observability Engineer

🚀 Data Quality / Observability Engineer (Seattle, WA – Hybrid, 2–3 Days Onsite)
Location: Seattle, WA (Local candidates only)
Work Arrangement: Hybrid – 2–3 days per week onsite
Employment Type: W2 Contract (U.S. Citizens & Green Card holders only)

✨ About the Role
We are seeking a Data Quality / Observability Engineer to own the monitoring, alerting, lineage, and SLA reporting layer across all ingestion pipelines. This role ensures Boeing has full visibility into pipeline health, data freshness, and SLA compliance — detecting and escalating issues before they impact downstream consumers.

🔧 Key Responsibilities
Implement pipeline-level metrics collection (records in/out, lag, throughput, failures, freshness).
Build and maintain monitoring dashboards in CloudWatch and/or Grafana.
Configure alerting thresholds tied to SLAs; ensure alerts trigger appropriately.
Capture data lineage and metadata; publish to Boeing’s Data/Developer Portal.
Design and implement data quality rules (completeness, schema conformance, freshness).
Produce automated SLA reports (weekly/monthly) with success rates, incident counts, and trend analysis.
Develop cost monitoring views for ingestion compute spend; provide optimization recommendations.
Collaborate with Boeing’s monitoring/observability team for dashboard and alerting integration.
Support incident triage with pipeline health diagnostics and root cause data.
Maintain and evolve DQ/observability standards as new sources are onboarded.

📌 Required Skills & Qualifications
5–7 years in data quality engineering, observability, or data operations.
Hands-on experience with CloudWatch (metrics, logs, alarms, dashboards) and Grafana.
Strong experience with data quality frameworks (Great Expectations, dbt tests, Deequ, Soda).
Familiarity with data lineage/cataloging tools (AWS Glue, Apache Atlas, DataHub, OpenLineage).
Proficiency in SQL and Python for metrics collection and automation.
Experience building SLA dashboards and automated reporting.
Knowledge of AWS cost monitoring tools (Cost Explorer, CUR, CloudWatch billing metrics).
Strong communication skills for SLA reporting and stakeholder presentations.
Experience collaborating with data governance teams on contracts and quality rules.

🌟 Preferred Skills
Experience with dedicated observability platforms (Monte Carlo, Datafold, Bigeye).
Familiarity with OpenTelemetry or distributed tracing for pipelines.
Exposure to FinOps practices for cost optimization.