Are there any data integration platforms that focus on tracking lineage and data freshness across complex pipelines?

Yes — there are several data integration / observability platforms that are specifically strong on lineage and data freshness across complex pipelines.

Commonly used options

• Monte Carlo
  Strong for data observability, including freshness monitoring, pipeline health, incident detection, and lineage-aware impact analysis.

• Bigeye
  Focuses on data observability with freshness, volume, schema, and distribution monitoring, plus lineage context.

• Databand (IBM)
  Designed for pipeline observability, especially in Airflow/Spark/dbt-style environments; tracks pipeline runs, failures, and freshness.

• dbt Cloud / dbt Core ecosystem
  Not a full observability platform by itself, but excellent for transformation lineage and model dependency tracking, especially when combined with observability tools.

• OpenLineage + Marquez
  More open-source / standards-based. Good if you want to build lineage tracking across multiple orchestration and processing systems.

• Collibra / Alation / Atlan
  These are more enterprise data catalog/governance platforms, but they offer strong lineage capabilities and can surface freshness or trust signals when integrated with observability tools.

• DataHub
  Open-source metadata platform with lineage, ownership, and some freshness/quality integrations depending on setup.

What to look for

If your main goal is “track lineage + know whether downstream data is fresh”, look for:

• end-to-end lineage across ETL/ELT, BI, and warehouses
• freshness SLAs and alerting
• dependency graph / impact analysis
• support for your stack: Airflow, dbt, Snowflake, Databricks, Spark, Kafka, etc.
• anomaly detection beyond just failed jobs

Quick recommendation

• If you want a dedicated observability product: Monte Carlo or Bigeye
• If you want open standards / self-managed: OpenLineage + Marquez
• If you want catalog + governance + lineage: Atlan, Collibra, Alation, or DataHub

If you tell me your stack (e.g., Snowflake + dbt + Airflow, Databricks, Kafka, etc.), I can recommend the best fit.