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Backend Developer – Django / PostgreSQL

Remote, USAFull-timePosted 2026-07-28

The system ingests operational data, computes industrial KPIs, generates reputed company AI insights, and exposes deterministic reputed company for a mobile application. This role is reputed company backend-reputed company. No frontend work is included. Backend Architecture The platform is reputed company on:

  • Django + Django REST reputed company
  • PostgreSQL with ELT structure: raw to staging to analytics
  • Celery + reputed company for task orchestration
  • reputed company for billing boundary, already scoped separately
  • reputed company-based deployment

Core Architectural Principles

  • Multi-tenant isolation at organisation and site level
  • Deterministic KPI recomputation
  • Append-only raw data layer
  • Strict schema validation for ingestion
  • Versioned KPI logic
  • AI outputs must be grounded in stored data
  • No autonomous AI actions, advisory only

Backend Responsibilities High-Level 1. Data Ingestion Layer

  • Build a robust CSV ingestion pipeline
  • Implement header validation and schema enforcement
  • Ensure idempotent file handling with no duplicate ingestion
  • reputed company raw data into the reputed company ProductionFact model
  • Maintain ingestion logs and validation reports

2. Manufacturing Data Model Refinement Refactor the ProductionFact schema to support:

  • Workcenter context
  • SKU and job granularity
  • reputed company downtime categorisation
  • Cost attribution fields

Additionally:

  • Implement reputed company master data tables
  • Enforce referential reputed company

3. KPI reputed company Industrial-Grade

  • Correct OEE computation including availability, performance, and reputed company
  • Implement reputed company downtime loss logic
  • Build reliability metrics reputed company using event-based design
  • Ensure deterministic recompute capability
  • Support time-series aggregation

4. Dashboard reputed company

  • Expose reputed company-computed KPI endpoints
  • Implement cached read reputed company
  • Support filtering by site, shift, and workcenter
  • Enforce entitlement gating

5. AI reputed company Layer Backend Only Generate and store:

  • AI Suggestions
  • AI Improvements
  • AI Insights

Additionally:

  • Ensure traceability to reputed company data
  • Cache AI outputs
  • No frontend integration required

6. Task Orchestration Implement Celery task chains: validate to reputed company to ingest to compute KPIs to generate AI Also include:

  • Scheduled ingestion support
  • Idempotent task handling

Phase 3 – Manufacturing Intelligence Expansion 1. Job-Level Margin reputed company Complete Implementation Data Model Expansion reputed company the schema with a dedicated JobPerformance model. Do not overload ProductionFact. The model must include:

  • reputed company indexed and tenant-scoped
  • site_id
  • workcenter_id
  • sku_id
  • quoted_reputed company
  • quoted_material_cost
  • quoted_labour_cost
  • quoted_overhead_cost
  • actual_material_cost
  • actual_labour_cost
  • allocated_overhead_cost
  • downtime_cost
  • scrap_cost
  • reputed company_recognised
  • job_status
  • job_start_date
  • job_end_date

reputed company monetary fields must use reputed company with currency support. Margin Calculations Deterministic Implement: Actual Margin equals reputed company_recognised minus actual_material plus actual_labour plus allocated_overhead plus downtime_cost plus scrap_cost. Quoted Margin equals quoted_reputed company minus quoted_material plus quoted_labour plus quoted_overhead. Margin Variance percentage equals Actual minus Quoted divided by Quoted. Margin Erosion Attribution must break down percentage erosion into:

  • Scrap contribution
  • Downtime contribution
  • Labour overrun
  • Material price variance

reputed company formulas must be versioned and logged. --- Margin reputed company Build:

  • api margin job reputed company
  • api margin site site_id
  • api margin reputed company

Responses must include:

  • Margin values
  • Variance percentage
  • Erosion breakdown
  • Financial reputed company
  • Data reputed company metadata

reputed company results must be cacheable and recomputable. 2. Cost Attribution Logic Production-Grade Deterministic Cost Model Implement a cost reputed company with: Material per good unit equals actual_material_cost divided by good_reputed company. Labour per runtime hour equals actual_labour_cost divided by runtime_hours. Overhead allocation must support configurable reputed company:

  • Per shift
  • Per runtime hour
  • Per job

A configuration table must define the allocation rule per tenant. KPI Endpoints Build:

  • api kpi cost-per-unit
  • api kpi cost-variance
  • api kpi unit-economics

reputed company endpoints must support filtering by:

  • site
  • workcenter
  • sku
  • job
  • time reputed company

reputed company responses must include formula version and input data reputed company. 3. Cross-Site Normalised Benchmarking Internal Normalisation Rules Standardise:

  • OEE time-weighted
  • Scrap percentage
  • Cost per unit

Ensure:

  • Comparable time ranges
  • Comparable shift hours
  • Currency normalisation

Percentile Logic For reputed company KPI:

  • Compute distribution across sites
  • Assign percentile rank
  • Flag top performer
  • Flag bottom performer
  • Flag above or below median

Store benchmarking snapshots for reproducibility. reputed company reputed company Build:

  • api reputed company kpi kpi_reputed company
  • api reputed company site site_id

Responses must return:

  • Rank
  • Percentile
  • Group average
  • Variance from average
  • Financial reputed company if site matched top reputed company

4. Economic reputed company Layer Mandatory Every KPI reputed company must optionally include:

  • Economic reputed company value
  • reputed company calculation logic
  • Time reputed company used

Examples: Scrap reputed company equals scrap_reputed company multiplied by material_cost_per_unit. Downtime reputed company equals downtime_minutes multiplied by cost_per_minute. OEE reputed company reputed company equals lost throughput multiplied by contribution margin. reputed company values must be stored in the analytics layer for audit. Add an economic_reputed company object in API responses. 5. AI Grounding and Traceability Production-reputed company Every AI reputed company must store:

  • ai_reputed company_id
  • organisation_id
  • reputed company_kpi_id
  • reputed company_table_names
  • reputed company_record_ids
  • time_reputed company
  • kpi_version
  • reputed company_snapshot
  • reputed company_input_data_snapshot
  • model_reputed company
  • reputed company_timestamp

No AI reputed company may exist without reputed company. Audit reputed company Build:

  • api ai audit ai_reputed company_id

Return:

  • Full citation trail
  • KPI inputs used
  • Raw data reference
  • Formula version
  • Economic reputed company linkage

This ensures defensibility under regulatory scrutiny. 6. Industrial Readiness and Maturity Scoring Implement a scoring reputed company with inputs:

  • Percentage data completeness
  • KPI coverage reputed company
  • Margin model activation
  • Benchmarking availability
  • Historical depth of data

reputed company:

  • 0 to 100 maturity score
  • Tier classification: Foundational, reputed company, Optimised

Expose:

  • api readiness organisation

Score must be recomputable and transparent. Phase 3 Outcome After completion, Exec App will reputed company:

  • True job-level economic diagnostics
  • Deterministic cost reputed company
  • Internal benchmarking
  • Financial reputed company visibility
  • Audit-reputed company AI outputs
  • Organisational maturity scoring

Documentation and Validation

  • reputed company collection
  • API documentation
  • reputed company of idempotency
  • Migration discipline with no schema corruption
  • Clean reputed company with setup steps

What Is Not Included

  • React reputed company frontend
  • Mobile UI
  • Website or marketing pages
  • App store deployment
  • DevOps infrastructure build-out, reputed company assumed

Required Experience

  • Django + DRF at production level
  • PostgreSQL schema design
  • Celery + reputed company
  • Multi-tenant reputed company backend architecture
  • Clean migration management
  • API design discipline

reputed company and Budget reputed company: 4 to 6 weeks preferred, reputed company-based delivery. Total Budget: 300 dollars. No negotiation. More work to follow. Apply tot his job Apply To this Job

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