At Billie.io, a Berlin-based startup reinventing how businesses handle payments, data plays a critical role in delivering fast, seamless financial services.

Billie provides small and medium-sized businesses (SMEs) with instant invoice financing, so they don’t have to wait months to get paid. But behind the scenes, ensuring smooth operations requires a sophisticated data pipeline — one that’s automated, efficient, and cost-effective. That’s where Fivetran and Apache Airflow come in.

Automating data ingestion with Fivetran

Billie pulls data from multiple sources — Google Analytics, Salesforce, its production database, LinkedIn, Facebook, and more — to fuel decision-making and analytics. Instead of managing these integrations manually, Billie uses Fivetran to automate data ingestion into Snowflake.

“We fully rely on Fivetran to handle data ingestion so we can focus on more complex workflows,” says Igor Chrivelband, Vice President of Data at Billie.io. “It’s reliable and takes a huge burden off our team.”

Why Billie uses Airflow for orchestration

While Fivetran moves data into their warehouse, Billie needs more control over the timing and execution of transformations. That’s where Airflow comes in.

Airflow is an open-source tool that lets teams schedule and monitor workflows, ensuring data processing happens at the right moment and in the right order. While many Fivetran connectors work out of the box for Billie, Airflow plays a key role in managing the ETL (Extract, Load, Transform) process for their production database — determining when to sync data, apply transformations, and trigger reports.

Chtivelband structures these steps as “segments” that can be dynamically scheduled and adjusted in Airflow. For example, the Fivetran segment, responsible for extraction and loading, can run separately from the transformation layer to prevent latency issues, SLA violations, or premature data processing.

“That’s where Airflow is particularly useful,” says Chtivelband. “We use both Fivetran and Airflow because they complement each other — Fivetran handles data ingestion, while Airflow acts as the orchestrator. It ensures data sync from sources like Google Analytics to our data warehouse at the right time, keeping everything efficient and in order.”

Airflow gives Chtivelband’s team at Billie fine-grained control over when things happen and visibility into pipelines, their dependencies, and their execution. This allows the coordination of data transformations across incoming data sources.

Smarter scheduling = lower costs

One of Billie’s biggest wins with Airflow? Cost savings.

During business hours, key data pipelines run every 5 minutes to keep analytics fresh. But outside of business hours, Billie reduces the frequency to every two hours — significantly cutting down on Snowflake compute costs.

“A simple shift from a 5-minute to a 2-hour sync cuts our costs by about 20%,” Chtivelband notes. “It’s a no-brainer. We save money, reduce resource consumption, and lower our environmental impact.”

How Billie uses Airflow’s operators and sensors

To take things further, Billie taps into Airflow’s powerful features:

• Operators are used to execute tasks in Airflow. For Fivetran, this means a FivetranOperator starts a Fivetran data sync. The flexibility of Airflow's scheduling allows Billie to easily and dynamically change when a FivetranOperator is called, giving them fine control of their data warehousing costs.
• Sensors will check to see if a certain criteria is met before they complete and let their downstream tasks execute. A FivetranSensor will monitor the status of a Fivetran sync and allow the DAG to progress as soon as data has been fully loaded into a warehouse. “This gives us an ability to understand if the sync is done or not, and if it’s done, do something immediately in Airflow,” Chtivelband says.

Together, Billie uses these tools for report scheduling — a smart workflow to ensure that data is fully synced and available before running a reporting process on top of Snowflake.“We have time-critical reports every morning,” Chtivelband explains. “We can’t send them until the data is available. Using Sensors is much better than blindly pulling every 5 minutes.”

Who should use Airflow + Fivetran?

If your team is managing complex data workflows, orchestrating Fivetran with Airflow can bring major efficiency gains. Chtivelband’s advice? Start small.

“I would say it's one of the cases when the appetite comes with food. Once you migrate from traditional data warehouse technologies like Teradata to Snowflake, you realize how much easier it is. The next step is Fivetran and dbt. My recommendation is to try cherry picking an easy experiment, and then if it works, then it's easier to become convinced. You can also show it to your boss like, "We've achieved this in one week, and our data analysts are happy."
— Igor Chtivelband, Vice President of Data at Billie.io

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