Engagement Type: Fixed-Price Contract (3–4 Weeks + 1 Week Post-Launch Support)
Overview
We are seeking an exceptionally strong Data Engineering Specialist to build a production-grade operational monitoring and analytics layer on top of our existing Google Cloud data stack.
This is not a discovery-heavy engagement.
The project is fully specified and documented. All alert logic, thresholds, dashboard requirements, schemas, and technical expectations are defined.
We need someone who can:
- Read detailed specifications
- Translate them into clean, production-ready data workflows
- Implement advanced SQL logic in BigQuery
- Build robust Dagster jobs
- Create operational dashboards that drive decision-making
- Deliver within a tight timeline
This role is execution-focused and suitable only for engineers with deep experience in data systems and production orchestration.
What You Will Build
You will deliver two production systems on top of our existing BigQuery warehouse.
Part A — Automated Operational Alert System
An automated monitoring system that continuously evaluates the health of our order pipeline and triggers notifications when predefined conditions occur.
Core Responsibilities
You will:
- Implement 11 automated alert rules as scheduled Dagster jobs
- Write advanced SQL queries against BigQuery (window functions, CTEs, rolling baselines, joins across multiple datasets)
- Implement anomaly detection logic using rolling comparisons
- Integrate Slack API for structured, formatted alerts
- Integrate SMS notifications (Twilio or similar) for critical-level alerts
- Implement structured logging and audit trails
- Store configurable alert thresholds in BigQuery (no hard-coded values)
- Ensure system reliability, idempotency, and clean error handling
Alert Categories Include
- Delayed orders
- Stuck pipeline stages
- SLA breaches
- Partner performance degradation
- Volume anomalies vs rolling baselines
- Failure spikes
- Operational bottlenecks
The alert system must be production-ready, observable, and maintainable.
Part B — Operational Dashboard (Looker Studio)
You will build a 4-page operational dashboard connected directly to BigQuery.
This dashboard will be used daily by the operations team to monitor pipeline health and partner performance.
Dashboard Pages
Real-Time Operations Overview
- Pipeline status
- Active orders by stage
- SLA compliance summary
- Stuck orders
- Critical alerts
Partner Performance Tracking
- Doctors, pharmacies, carriers
- Trend analysis
- SLA adherence
- Throughput metrics
Historical Trends & Anomaly History
- Rolling baselines
- Alert frequency trends
- Performance over time
Detailed SLA Compliance Reporting
- Breach tracking
- Time-to-resolution metrics
- Drill-down capability
- The dashboard must include:
- Filters
- Drill-down capability
- Trend visualizations
- Clear operational storytelling
Technology Stack (Already in Place)
You will work within our existing infrastructure.
- Google BigQuery – Primary data warehouse
- Dagster – Production orchestration tool
- Python – For alert logic and orchestration
- SQL (Advanced) – Complex transformations and aggregations
- Looker Studio – Dashboard development
- Slack API – Alert notifications
- SMS (Twilio or equivalent) – Critical alerts
- Google Cloud Platform (GCP) – Cloud environment
No infrastructure setup required. You will build within our existing systems.
Mandatory Requirements (Non-Negotiable)
Only apply if you meet ALL of the following:
Technical
- Strong Python in a data engineering context (not web development)
- Advanced SQL proficiency:
- Window functions
- CTEs
- Rolling aggregations
- Complex joins
- Performance optimization in BigQuery
- Proven Google BigQuery experience
- Experience with Dagster OR strong Airflow/Prefect experience (Dagster preferred)
- Experience building multi-page Looker Studio dashboards connected to BigQuery
- Slack API or webhook integration experience
- Experience working within Google Cloud Platform
Professional
- Ability to read detailed specifications and execute independently
- Strong production mindset (logging, error handling, idempotency)
- Clear communication in async environments
- Structured documentation habits
- Experience delivering under time-bound milestones
- If you do not have hands-on BigQuery + orchestration experience, this role is not suitable.
Nice-to-Have (Strong Advantage)
- Healthcare or e-commerce pipeline experience
- Shopify data familiarity
- SMS integrations (Twilio)
- Experience building operational monitoring systems
- Experience designing anomaly detection logic
- Experience with SLA tracking frameworks
Timeline & Milestones
This is a 3-week build with a 1-week support buffer.
Week 1 (Days 1–5)
- Environment familiarization
- Core alert rule implementation
- Slack integration
- Initial production deployment
Milestone: Core alerts live
Week 2 (Days 6–9)
- Anomaly detection logic
- SMS integration
- Logging framework
- Configurable thresholds
- Full system testing
Milestone: Alert system complete
Week 3 (Days 10–13)
- 4-page Looker Studio dashboard
- Testing and validation
- Documentation and handover
Milestone: Dashboard live, project complete
Post-Launch (1 Week)
- Threshold tuning
- Minor refinements
- Operational adjustments
Engagement Structure
- 1 month Fixed-price contract
- Nigeria-based consultant
- Fully remote
- Daily async updates via email
- Full system access provided on Day 1
- Detailed specification documents shared with shortlisted candidates
- 1-week post-launch support required
What You Must Submit
To be considered, your application must include:
Your CV
A concise summary of relevant experience:
- BigQuery
- Dagster/Airflow/Prefect
- Alerting systems
- Looker Studio dashboards
- Example of a production pipeline you built:
- Dagster or Airflow preferred
- Brief explanation of architecture
- Example of a Looker Studio dashboard:
- Screenshot or link
- Brief explanation of data model
- Your fixed-price quote
- Confirmation of availability for the 3-week timeline
- Applications without concrete examples will not be reviewed.
Ideal Candidate Profile
You are:
- A senior-level data engineer
- Comfortable working directly in BigQuery
- Experienced with orchestration tools
- Detail-oriented and systematic
- Able to build reliable monitoring systems
- Strong in operational thinking
- Comfortable working independently with minimal hand-holding
If you are confident in your ability to execute this project at a high technical standard within the stated timeline, we encourage you to apply.
This is a high-impact build that will directly power our operational decision-making systems.
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