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Data pipelines
ETL/ELT pipelines that move data reliably from sources to destinations. Automated, monitored and built to handle growth without breaking.
AvailableTaking new engagements · Q2 2026
All servicesService · Data · 06
Raw data intocompetitive advantage.
Data infrastructure that scales from day one — pipelines, warehouses, analytics and insights so you make better decisions faster than the competition.
- Realtime
- Pipelines available
- Self-svc
- Dashboards
- Schema
- Versioned, tested
- EU/US
- Residency options
What we build · 06 capabilities
Data infrastructure that grows with you.
Pipelines, warehouses, real-time processing, BI, governance — designed to remain understandable past your first hundred employees.
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Data warehousing
Centralized storage optimized for analytics. Query billions of rows in seconds with proper indexing, partitioning and schema design.
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Real-time processing
Stream processing for live data — event tracking, real-time dashboards, instant alerts. See what's happening now, not yesterday.
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Analytics & BI
Self-service dashboards and reports that answer business questions. No SQL required — your team gets data access without bottlenecks.
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Data APIs
Expose your data through clean, performant APIs. Let other systems consume the insights they need with auth and rate limiting.
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Data governance
Access controls, audit logs, data quality monitoring and compliance. Keep data secure and meet regulatory requirements.
How we work · 04 stages
Extract, transform, act.
- Stage / 01
Map sources
We catalog every database, SaaS tool and event stream — and decide which actually matter for the decisions on the table.
- Stage / 02
Ingest & model
Reliable, idempotent ingestion. Dimensional / dbt-style models that your analysts can read, change and trust.
- Stage / 03
Expose & visualize
Dashboards for operators, APIs for engineers, exports for finance. The data shows up in the tools each team already uses.
- Stage / 04
Govern & improve
Lineage, freshness alerts, PII tagging and access reviews — data quality stays a metric, not a vibe.
Modern data stack
Best-in-class tools, sensibly assembled.
- Postgres
- Snowflake
- BigQuery
- Redshift
- ClickHouse
- dbt
- Airbyte
- Fivetran
- Kafka
- Airflow
- Dagster
- Apache Spark
- Looker
- Metabase
- Superset
- Grafana
Why teams pick us
Trustworthy data, without the spreadsheet sprawl.
Most data infra collapses under its own complexity within 18 months. We design for explainability — schemas that a new analyst can read on their first day, pipelines that show their work.
- i.
Schemas you can read
Naming, comments, dbt docs and lineage. Your data is not a haunted house.
- ii.
Freshness as SLO
Each dataset has a freshness budget. Misses page someone. Stale data is a bug, not a fact of life.
- iii.
Cost-aware design
Warehouse cost grows linearly with care — exponentially without it. We design with both knobs in view.
Common questions
What teams ask before they build.
Depends on existing cloud, query patterns and team familiarity. We pick the one that minimizes total cost of ownership for your specific workload — not the one we sell most.