Our ambition is to build a best-in-class data infrastructure to scale the Product-Led Growth SaaS company that is Pitch - therefore we’re looking for a Senior Data Engineer for our growing centralized Data Engineering team. Our mission is to deliver a lean and reliable data foundation that enables informed decision making for our many internal customers across Finance, Customer Operations, Sales, Marketing and more.

We are in the middle of a migration, and our Data Warehouse and transformation pipelines are still on a nascent state. As a Senior Data Engineer, you will be contributing to our key goal of setting up a data platform foundation that will scale with the business. You will help evolve Pitch and the infrastructure it uses to make sure that decisions can always be driven by high quality data.

Future and current challenges involve scalability and experimentation and driving substantial change in the way we make better and more informed decisions.

What you'll get to do:

• Plan and support the buildout of our Snowflake data warehouse, and future-proof it for scale.
• Leverage the right tools to enable the team to build a lean infrastructure that delivers testable, maintainable, and modern data solutions.
• Take the lead on implementing best practices with regards to moving infrastructure from vendor-based to in-house or open-source.
• Integrate data ingestion tools and automate data quality checks.
• Implement and own our data warehouse management and other systems' monitoring.
• Play a lead role in contributing to our experimentation tooling.

What you should bring:

• At least 3-5 years' experience with Data Warehouse Management and/or Cloud Platform development, ideally within a product-minded SaaS or Tech company.
• Experience in pipeline orchestration using modern Big Data tools and architectures.
• Deep understanding of Data Warehouse management with Snowflake, Redshift and/or BigQuery.
• Solid cloud platform experience with Amazon Web Services or Google Cloud Platform.
• Infrastructure as code experience with CloudFormation or Terraform.
• Exposure to DevOps workflows.
• Proficiency in Python for data processing, and SQL for building data transformation.
• Strong interest in working on foundational infrastructure and automation practices.
• Ability to handle multiple competing priorities in a fast-paced, product-led growth SaaS company.
• Strong cross-functional working and communication skills, and the ability to work within a centralized team.
• Growth-focused and product-minded attitude.

Nice-to-haves:

• You've built out data infrastructure from scratch (or nearly from scratch) at a fast-growing startup.
• Experience working with events and its definition (schema registry)
• Experience with data catalog, data lineage and data discovery solutions
• Experience with data integration tools like Fivetran or Airbyte.
• Experience with orchestration technologies Airflow or Luigi.
• Experience with behavioural analytics tools (either internal or 3rd-party tools such as Google Analytics, Snowplow, Segment or Amplitude).
• Experience with reverse ELT tools like Hightouch or Census.
• Experience with experimentation frameworks.
• Experience with dbt.