ETL Pipeline Development
Data pipelines that run reliably at any scale.
We build data pipelines that extract from any source, transform with business logic, and load into your warehouse or lake. Orchestrated with Airflow, tested, monitored, and built to handle growth.
- Extract from APIs, databases, files, and streaming sources
- Transform with Spark, dbt, or Python at any scale
- Load to Snowflake, BigQuery, Redshift, or data lakes
- Apache Airflow orchestration with alerting
- Data quality checks and lineage tracking
- Incremental loads and backfill capabilities
Data pipelines that run reliably at any scale.
Data Engineering
Technologies We Use
Modern data stack for reliable, scalable pipelines
What we deliver
Production-ready data pipelines with documentation, monitoring, and knowledge transfer.
Data pipeline code
Well-tested Airflow DAGs, Spark jobs, or dbt models in version control with CI/CD.
Orchestration setup
Managed Airflow or Dagster deployment with schedules, alerting, and retry logic.
Data quality framework
Automated checks for schema changes, null rates, freshness, and business rule validation.
Documentation & runbooks
Technical documentation, data dictionaries, and operational runbooks for your team.
How We Work
A systematic approach to building data pipelines that last.
Data Discovery
Map your data sources, understand schemas, identify transformation needs, and define target models.
Pipeline Architecture
Design pipeline DAGs, choose tools, plan for scale, and establish testing and monitoring strategies.
Build & Test
Implement pipelines with comprehensive testing, data quality checks, and documentation.
Deploy & Monitor
Production deployment with alerting, SLA tracking, and runbooks for your team.
Engagement models
Flexible options from single pipelines to full data platform builds.
Pipeline sprint
Single data pipeline from source to warehouse with testing and monitoring.
$15,000 - $25,000
Data platform build
Multiple pipelines, orchestration platform, data quality framework, and team training.
$40,000 - $60,000
Managed data engineering
Ongoing pipeline development, maintenance, and optimization for your data platform.
$8,000 - $18,000/mo
Certifications & Partners
What clients are saying
Results from data pipeline implementations we've delivered.
"Reports that used to be 3 days stale now update hourly. The business finally trusts the numbers."
"We went from 47 manual data jobs to 12 automated pipelines. Freed up 2 FTEs for actual analysis."
"The data quality checks catch issues before they hit dashboards. No more embarrassing board meeting corrections."
Frequently asked questions
Should we use ETL or ELT?
Modern cloud warehouses favor ELT (Extract-Load-Transform) since they can handle transformation at scale. We recommend ELT for most use cases, with ETL reserved for sensitive data that needs transformation before loading.
Do we need Airflow or can we use simpler tools?
For simple, low-frequency pipelines, tools like Fivetran or AWS Glue may suffice. Airflow adds value when you have complex dependencies, custom logic, or need fine-grained control. We assess during discovery.
How do you handle pipeline failures?
Pipelines include automatic retries, alerting, and idempotent design so reruns don't create duplicates. We also build backfill capabilities for historical data reprocessing.
Can you work with our existing data tools?
Yes. We integrate with existing warehouses, BI tools, and orchestrators. If you're already using Snowflake, dbt, or Looker, we build pipelines that feed those systems.
Ready to build reliable data pipelines?
Share your data sources and goals. We'll assess architecture, tooling, and timeline in a 30-minute call.
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