Data Engineering & Analytics
Data pipelines, warehouses, and analytics that actually ship.
Service Overview
Transform fragmented data into actionable insights. We build the data infrastructure your business depends on—from ETL pipelines to real-time analytics dashboards.
What you get with this service.
ETL/ELT pipelines with Airflow, dbt, and Fivetran
Modern data warehouses: Snowflake, BigQuery, Redshift
Real-time data streaming with Kafka and AWS Kinesis
Self-serve analytics dashboards and BI tools
Data quality monitoring, governance, and lineage tracking
Machine learning data pipelines and feature stores
In-depth capabilities & implementation.
Your data is scattered across Salesforce, Stripe, your production database, Google Sheets, and three other SaaS tools. Your team spends hours weekly pulling reports manually. Leadership asks questions you can't answer without a two-day data pull. Sound familiar?
We build the data infrastructure that fixes this for custom enterprise software platforms. Automated pipelines pulling data from every source, cleaning and transforming it, loading it into a centralized warehouse. Then we build dashboards and BI tools your team actually uses.
Data Engineering Services: - Data Pipelines: Automated ETL/ELT from any source to any destination - Data Warehousing: Snowflake, BigQuery, Redshift architecture and optimization - Real-Time Streaming: Kafka, Kinesis for event-driven architectures (powering systems like our [Guardian ML real-time fraud detection engine](/projects/guardian-ml/)) - Analytics & BI: Looker, Tableau, Metabase, custom dashboards - Data Quality: Automated testing, monitoring, alerting on data issues - Data Governance: Lineage tracking, access controls, compliance
Real-World Scale: We've built data platforms processing millions of events daily (such as the [Affinity Engine deep learning recommender](/projects/affinity-engine/)), warehouses handling terabytes of historical data, and real-time dashboards updating every 30 seconds. Learn more about [measuring AI data pipeline ROI](/blog/measuring-roi-ai-automation-2026/).
Modern Data Stack: - Ingestion: Fivetran, Airbyte, custom connectors - Transformation: dbt (data build tool), SQL, Python - Orchestration: Apache Airflow, Prefect, Dagster - Storage: Snowflake, BigQuery, Redshift, S3 data lakes - Visualization: Looker, Tableau, Metabase, custom React dashboards - Quality: Great Expectations, Monte Carlo, custom monitoring
Need a custom scope?
Talk directly with a senior developer. We'll audit your requirements and provide a clear timeline & fixed proposal.
Schedule 30-Min CallHow we execute & deliver your project.
Week 1: Audit your data sources, map what you have, identify what questions leadership needs answered.
Week 2-4: Build core pipelines—pulling data from key sources into a warehouse, with basic transformations and quality checks.
Week 5-8: Build dashboards and BI layer. Self-serve analytics so your team answers their own questions without waiting on engineering.
Ongoing: Expand to additional data sources, add more sophisticated transformations, optimize performance.
You get a system that's maintainable, well-documented, and doesn't break when someone changes a Salesforce field.
Who this service is engineered for:
Expected key outcomes & metrics:
Single pane of glass for leadership decision-making
Sub-minute data freshness for real-time insights
Compliance-ready data lake with full governance
80% reduction in manual reporting time
Frequently Asked Questions.
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Start your Data project with our senior engineering studio.
Book a free 30-minute scoping call. A senior technical partner will review your requirements and provide a clear timeline and ballpark estimate.