Data Engineering
Data infrastructure that drives decisions.
Zarsco builds data pipelines, warehouses, and analytics platforms that turn raw data into actionable business intelligence. From ETL design to real-time streaming, we architect data infrastructure that scales with your business.
Unified Data Platform
Single source of truth connecting all your data sources — cloud, on-premise, SaaS.
Real-Time Data
Streaming pipelines for real-time dashboards, alerts, and instant insights.
Data Quality
Automated data validation, testing, and lineage tracking for reliable analytics.
Self-Service Analytics
Business teams can explore data independently without waiting for engineering.
What we do for you
Data Warehouse Build
Design and implement BigQuery, Snowflake, or Redshift data warehouses.
ETL / ELT Pipelines
Reliable data pipelines from databases, APIs, and SaaS tools to your warehouse.
Real-Time Streaming
Apache Kafka and Flink pipelines for real-time event processing.
Analytics Engineering
dbt models, semantic layers, and business metrics definitions.
Data Lakehouse
Delta Lake or Iceberg-based lakehouses for unified batch and streaming analytics.
Data Governance
Data catalogs, lineage, access control, and compliance for regulated industries.
Everything included in our Data Engineering service
We handle every aspect from strategy to launch so you can focus on outcomes, not execution.
- Data architecture design and review
- ETL/ELT with Airbyte, Fivetran, or custom pipelines
- dbt transformation layer
- Data warehouse on BigQuery, Snowflake, or Redshift
- Apache Kafka and Flink for streaming
- Data quality monitoring with Great Expectations
- Business intelligence with Looker, Metabase, or Tableau
- Data catalog and lineage with DataHub or OpenMetadata
Frequently Asked Questions
What data warehouse do you recommend?
BigQuery for GCP-centric teams with unpredictable query volumes. Snowflake for organizations needing maximum flexibility and multi-cloud. Redshift for AWS-native teams with steady, high-volume workloads.
How long does it take to build a data platform?
A focused data warehouse with core pipelines and dashboards takes 6–10 weeks. A comprehensive data platform covering multiple sources, real-time streaming, and governance takes 3–6 months.
Do you use dbt?
Yes. We use dbt (data build tool) as the standard transformation layer in our data stacks. It enables version-controlled, tested SQL transformations with full lineage tracking.
Can you work with our existing BI tool?
Yes. We integrate with Tableau, Power BI, Looker, Metabase, Superset, and other BI tools — connecting them to the data warehouse we build.
Ready to get started with Data Engineering?
Book a free consultation call. Our experts will assess your needs and outline a clear plan.