dbt is the de-facto transformation layer for modern data warehouses — and most dbt projects accumulate technical debt within 12 months (stale tests, ungoverned models, broken CI). NKKTech ships senior dbt consultants for greenfield projects, dbt rescue, MetricFlow semantic layer, exposures, and production-grade CI/CD. Works on Snowflake, BigQuery, Databricks, Redshift, Postgres. Fixed-scope from USD 15K. Singapore-law MSA.
Five engagement patterns dbt clients run most often. Most start with the 1-week audit (USD 4K fixed) before deeper work — that's where we identify whether you need bootstrap, rescue, or strategic refactor.
Forensic review of existing dbt project. Output: ranked findings with effort × impact. Common findings: untested sources, models with circular deps, missing exposures, broken CI gates, no semantic layer, untyped tests. Deliverable = prioritised remediation plan + dollar effort estimate.
Greenfield dbt project: source freshness checks, staging/intermediate/marts layering, naming conventions, dbt_project.yml config, packages (dbt_utils, audit_helper, codegen). Snowflake / BigQuery / Databricks / Redshift profile selection, CI/CD via dbt Cloud or self-hosted GitHub Actions runner.
Take over an existing dbt project with technical debt. Fix broken CI, add missing tests, refactor mega-models, document with dbt-docs, migrate to dbt Cloud or self-hosted runner. Output: dbt project that passes `dbt build --full-refresh` clean + senior-engineer-readable docs.
Implement MetricFlow (dbt's semantic layer, GA 2024). Define metrics in YAML, query via dbt-mf or Cube, expose to Looker/Tableau/Mode/Hex via Semantic Layer endpoint. Output: single source of truth for KPIs — no more 'why is the dashboard number different from the report'.
GitHub Actions or GitLab CI workflow for dbt: PR-triggered tests, full-refresh on merge to main, slim CI for cost savings, dbt-checkpoint pre-commit hooks, SQLFluff + sqlmesh-style state-aware deployment. Production-grade for teams of 5-50 analysts.
Monthly retainer: USD 6-12K with locked engineer hours. Senior dbt engineer on-call for new model requests, test triage, quarterly project hygiene reviews, MetricFlow semantic-layer evolution. Use case: data teams without a senior dbt-specialist hire.
Senior dbt engineer joins. Review your current dbt project (or greenfield needs). Top-3 friction points identified. Outcome: recommend entry-level engagement.
Singapore-law MSA + scoped SOW + fixed-fee quote. Lead engineer named. Deliverables list with passing-criteria for each milestone.
Weekly demo + written progress report. Milestone-based payment. Production handoff includes dbt-docs site, on-call runbook, exposure inventory.
30-day warranty (we fix any bugs free). Optional monthly retainer for ongoing ownership. Quarterly project-hygiene review if retainer engaged.
Product analytics + customer 360 dbt project: Segment events → staging → intermediate → marts (customer / subscription / event facts). MetricFlow for KPI consistency (MRR, ARR, churn, NPS) across BI tools.
Transaction warehouse dbt models for compliance reporting (BSA, EMIR, MiFIR). Audit_helper macros for regulator-ready reconciliation. Exposures linking to risk dashboards. Snapshots for transaction history.
Multi-source dbt project (Shopify + Stripe + Amazon + Tokopedia → unified). Currency conversion staging layer, cohort retention marts, recommendation feature stores feeding ML.
Metering dbt models: raw events → per-customer-per-day aggregates → billing-ready marts. Stripe billing integration via reverse-ETL. Critical for AI SaaS scale-ups tracking per-customer token spend.
Clinical-data dbt project on OMOP common-data-model. PHI de-identification staging layer, cohort definition marts, research-team exposures. HIPAA-aligned testing patterns.
Multi-touch attribution dbt project: ad-platform sources (Meta + Google + LinkedIn + TikTok) → unified spend marts. Time-decay attribution macros, channel ROAS models, MetricFlow for CAC/LTV.
Depends on team size + budget. dbt Cloud: faster onboarding, built-in IDE + scheduler, ~USD 100-1500/user/month. Self-hosted: full control, free, requires GitHub Actions / GitLab CI setup. We support both. For teams <5 analysts, dbt Cloud is usually worth it. For teams 5+ with engineering bandwidth, self-host often wins on cost.
Yes — this is our most-common dbt engagement. Common findings: missing source freshness, untested models, broken CI, no exposures, mega-model bottlenecks. Engagement size USD 25-60K, 4-8 weeks. Output: dbt build --full-refresh passes clean + senior-engineer-readable docs + remediation plan for remaining tech debt.
MetricFlow (GA 2024) is dbt's semantic-layer offering — define metrics in YAML once, query via dbt-mf or Cube, expose to BI tools. We've shipped MetricFlow for SaaS clients needing KPI consistency across Looker / Tableau / Hex. Implementation USD 30-90K depending on metric count + BI tool count.
Core: dbt_utils (utility macros), audit_helper (reconciliation), codegen (boilerplate). Observability: elementary (free) or Monte Carlo (paid). Testing: re_data, dbt-expectations. Governance: dbt-checkpoint, SQLFluff. We tailor recommendations to your stack — not a one-size-fits-all.
Yes. Incremental rescue pattern: audit first (1 week), fix highest-impact issues (2-4 weeks), then optionally refactor in phases (PRs reviewed by your team). We don't push a re-build unless the project is unsalvageable — incremental fixes are usually 60% cheaper and lower-risk.
Lead dbt engineer (10+ yrs SQL/dbt) + 1 mid-senior data engineer (5+ yrs) + 0.25 FTE PM. Hanoi-based. Direct Slack/GitHub access. dbt Cloud + GitHub Actions experience standard. JST/SGT/CET/EST timezone coverage.
NKKTech delivered our LLM document processing pipeline on time and exactly on budget. The tech lead was available on Slack daily. First offshore team that actually worked the way we expected.
Tony's team understood our legacy PHP system faster than our internal team. Zero downtime migration, exactly as promised. The bilingual PM made communication seamless.
We went from 15 hours/week of manual prospecting to fully automated lead gen in 8 weeks. ROI in 60 days as Tony promised.
NKKTech delivered our LLM document processing pipeline on time and exactly on budget. The tech lead was available on Slack daily. First offshore team that actually worked the way we expected.
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