Solutions
ETL Automation
Automate Extract-Transform-Load workflows across your entire data stack. LyftData replaces ad-hoc schedulers with a declarative control plane — Server orchestrates versioned Jobs,Workers execute transformations, and Run & Trace validates every run before production.
What It Does
LyftData replaces traditional ETL code with a declarative control plane. Jobs define each flow —Input → Actions → Output — while the Server schedules, validates, and observes execution across distributed Workers.
- ✓Ingest from S3, GCS, HTTP, or files without writing code.
- ✓Apply filters, parsers, enrichers, or masking through versioned YAML actions.
- ✓Route to destinations such as Snowflake, Splunk, Datadog, or S3.
How It Works
Each Job definition describes a data flow. When you deploy, the Server records the version, Workers run it, and Run & Trace lets you validate every step before production.
Define a single flow, then decide what gets loaded for analytics vs. archived for backfill and audit—without rewriting the pipeline.
Why Teams Choose LyftData for ETL
Faster Deployments
Declarative Jobs remove custom scripts so new flows go live in minutes, not weeks.
Built-in Reliability
Server manages retries, backoff, and monitoring — no external schedulers required.
Governed Outputs
Mask sensitive fields and track lineage automatically across every pipeline.
Integrated With Your Stack
Connect seamlessly to S3, GCS, Snowflake, Datadog, Splunk, and more.
