Own data assets and data pipelines that provide actionable insights into customer, product, GTM, and other key business functions
Design, develop and maintain scalable data pipelines and transformations using data from a variety of engineering and business systems (e.g., Salesforce/CPQ, NetSuite, Marketo)
Collaborate with Analysts to improve data models that feed business intelligence tools, increasing data accessibility and drive adoption of data
Deploy ML models together with Data Science teams according to best practices of ML life cycle, and improve our AI infrastructure
Implement processes and systems to manage data quality, ensuring production data is always accurate and maintains SLAs
Experience Requirements
Work experience building maintaining data pipelines on data-heavy environments (Data Engineering, Backend with emphasis on data processing, Data Science with emphasis on infrastructure)
Strong knowledge of Python required
Advanced working SQL knowledge and experience working with relational databases
7+ years experience with Data Warehousing Solutions (BigQuery, Redshift, Snowflake, Vertica, or similar)
7+ years experience with Data Pipeline Orchestration (Airflow, Dagster, Prefect, or similar)
Confidence in using Git, CICD, and containerization
Google Cloud Platform, AWS or Azure experience
Database architecture experience
Desired Skills
Experience with major B2B vendor integrations (Salesforce/CPQ, NetSuite, Marketo, etc.)
Good understanding of Data Modelling (Kimball, Inmon, SCDs, Data Vault, Anchor)
Knowledge of Python Data Libraries (Pandas/SciPy/NumPy/Sci-Kit Learn/TF/PyTorch)
Experience with Data Quality Tools, Monitoring and Alerting
Experience with Enterprise Data Governance, Master data management, Data Privacy and Security (GDPR, CCPA)
Familiarity with Data Streaming and CDC (Google Pub/Sub, Google DataFlow, Apache Kafka, Kafka Streams, Apache Flink, Spark Streaming, or similar)
Experience with building analytic solutions in a B2B SaaS environment
Experience partnering with go-to-market, sales, customer success, and marketing teams
Interpersonal skills
Good communication, collaborative demeanor and ability to work in distributed, multi-functional, multinational teams with the ability to articulate a point of view.
