Dashboards lie and AI hallucinates when the underlying tables are messy. We build monitored CDC pipelines, medallion dbt models and clean evaluation datasets across BigQuery, Snowflake, AWS and Postgres.
WHAT WE BUILD WITH DATA ENGINEERING
We connect your scattered software tools into one clean, tested data warehouse so leadership trusts the numbers and your AI assistants read accurate data.
BigQuery · Snowflake · Postgres · dbt End the Monday argument over whose Excel sheet is right. We unify Stripe, SAP/Logo/NetSuite, HubSpot and ad platforms into reconciled dbt tables.
Build our data warehouse
CDC · Airbyte · AWS Glue · PySpark We build monitored, idempotent pipelines that stream database changes (CDC) and API events in minutes, alerting Slack immediately if an upstream API changes.
Automate our data pipelines
Chunking · OCR · Deduplication · Vector DB AI is only as smart as the data you feed it. Our data engineers and supervised data interns clean, deduplicate, label and index your documents for RAG and ML.
Prepare our data for AI
HubSpot · Salesforce · Meta CAPI · Google Sync product usage, churn risk and real closed-won revenue from your warehouse straight into HubSpot and ad pixels so algorithms bid on real buyers.
Sync warehouse to CRM & ads
Partitioning · Clustering · Query Refactor Full-table scans and unpartitioned dbt models silently burn thousands of dollars. We partition, cluster and refactor slow queries in a 3-week sprint.
Cut our warehouse bill
Senior Data Engineer + Trained Interns Need thousands of product rows, messy legacy ERP tables or training samples cleaned and verified? Our supervised data pod handles the heavy lifting.
Hire a data cleaning podINTERACTIVE LINEAGE DAG
Capture row-level changes from Postgres/MySQL (Debezium/CDC) alongside Stripe, HubSpot and ad platform webhooks without impacting production database load.
-- CDC Stream Contract
source: postgres_wal_stream (slot: orzed_cdc)
deduplication_key: (event_id, lsn_offset)
on_schema_drift: alert_slack("#data-ops") + quarantine_extra_cols Every raw payload lands unmodified in partitioned Parquet / S3 / BigQuery Bronze tables so you can replay history from day one whenever business logic changes.
-- Bronze Partition Spec partition_by: DATE(_ingested_at) cluster_by: [tenant_id, event_type] retention: immutable_append_only (kms_encrypted = true)
Versioned dbt models strip internal test accounts, normalize currencies to UTC/USD and mask sensitive PII columns before analysts or AI pipelines read them.
SELECT
order_id,
tenant_id,
SHA256(LOWER(TRIM(customer_email))) AS customer_hash,
ROUND(amount_cents / 100.0, 2) AS net_revenue_usd
FROM {{ ref("brz_stripe_charges") }}
WHERE is_test_mode = FALSE AND status = "succeeded" One governed definition for Net Revenue, CAC, LTV and Cohort Retention powering executive BI scorecards with zero Monday-morning spreadsheet arguments.
-- dbt Semantic Exposure: fct_monthly_cohort_ltv
tests:
- dbt_utils.expression_is_true:
expression: "net_revenue_usd >= 0"
- reconciled_with_finance_ledger: { tolerance_usd: 0.01 } Push product-qualified lead scores and LTV back into HubSpot and Meta/Google CAPI, and feed clean, permission-tagged chunks into pgvector / Qdrant for RAG.
exposures: - hubspot_reverse_etl (sync: pql_score, churn_risk_shap) - meta_conversions_api (event: qualified_deal_won) - qdrant_rag_index (chunk_tokens: 512, acl_role_tag: required)
We refactor unpartitioned queries, add clustering keys and prune dead dbt models in a focused three-week sprint.
WHAT WE BUILD
Ads, CRM, billing, ERP and product databases synced automatically.
We replace fragile cron scripts and manual CSV exports with monitored pipelines (Airbyte, Fivetran, Kafka, AWS Kinesis/Glue or custom Python/PySpark workers) that alert Slack the moment a source drifts.
BigQuery, Snowflake, ClickHouse or Postgres modeled cleanly in dbt.
We structure raw, staging and mart layers in dbt with automated data-quality tests, documentation and partitioning/clustering so queries stay fast and warehouse bills drop by 30 to 60%.
Good AI starts with clean, permissioned, deduplicated data.
With our senior data engineers and supervised data interns, we build document chunking, metadata tagging, embedding refresh and 500-case evaluation sets that keep your AI accurate.
Push clean scores and segments back into HubSpot, Klaviyo and ad platforms.
A warehouse should not be a dead end. We sync product usage, health scores and LTV back into your CRM and ad platforms so sales and marketing act on live data.
WAYS TO START
Stand up a clean warehouse with your top 4 data sources and core dbt models.
End-to-end data platform powering both executive BI and grounded AI assistants.
A senior data engineer + data intern maintaining pipelines, cleaning datasets and cutting warehouse spend.
Adjacent disciplines
Executive scorecards and department views built on the Gold tables.
AIRAG assistants and document workflows fed by clean pipelines.
ModelsTraining, evaluation sets and feature stores built on your warehouse.
RevOpsReverse-ETL pushing product usage and LTV scores into your CRM.
Ingest · Model · Activate
Tell us your current sources and warehouse. We reply with an architecture plan and fixed scope within one business day.