We are looking for a seasoned, self-driven professional with a strong sense of ownership who can take a task from start to finish independently. We also value genuine intellectual curiosity – someone who keeps up with what's happening in the data and AI space, is willing to experiment, and helps the team identify where new technologies can create real value
How will you make an impact?
Design, build, and maintain scalable data pipelines feeding dashboards and analytical products across the R&D organization
Own and manage the cloud data warehouse – schema design, performance tuning, and access control
Manage data ingestion workflows connecting diverse data sources to the central data platform
Develop and maintain transformation models ensuring clean, well-documented, and tested data layers
Accompany the full data lifecycle from raw ingestion to business-ready datasets, and build the corresponding reports and dashboards where needed
Implement data quality checks, monitoring, and alerting to proactively identify and resolve issues
Translate business requirements into data solutions, working across R&D, Product, IT, and Business Operations
Explore emerging AI capabilities as they relate to data engineering and help identify practical opportunities for the team
How will you make an impact?
Design, build, and maintain scalable data pipelines feeding dashboards and analytical products across the R&D organization
Own and manage the cloud data warehouse – schema design, performance tuning, and access control
Manage data ingestion workflows connecting diverse data sources to the central data platform
Develop and maintain transformation models ensuring clean, well-documented, and tested data layers
Accompany the full data lifecycle from raw ingestion to business-ready datasets, and build the corresponding reports and dashboards where needed
Implement data quality checks, monitoring, and alerting to proactively identify and resolve issues
Translate business requirements into data solutions, working across R&D, Product, IT, and Business Operations
Explore emerging AI capabilities as they relate to data engineering and help identify practical opportunities for the team
Requirements:
At least 5 years of hands-on, production data engineering experience
Proven expertise with a cloud data warehouse (Snowflake)
Hands-on experience with a data ingestion tool (e.g., Fivetran or equivalent)
Hands-on experience with a data transformation framework (e.g., dbt or equivalent)
Strong SQL skills: advanced querying, optimization, and data modeling
Strong hands-on experience working with external APIs, including authentication, rate limits, pagination, and error handling
Ability to design, build, and maintain custom API-based data ingestion pipelines in Python
Hands-on experience with Python for data engineering tasks
Practical experience operating workflow orchestration tools such as Airflow
Ownership and administration of cloud data environments such as AWS or Azure, including account-level responsibility for data workloads
A strong sense of accountability – comfortable being the go-to person for your data domains and available to respond when issues arise outside of regular hours
Genuine curiosity about developments in the AI and data space – someone who actively follows trends, is eager to experiment, and brings new ideas to the table
At least 5 years of hands-on, production data engineering experience
Proven expertise with a cloud data warehouse (Snowflake)
Hands-on experience with a data ingestion tool (e.g., Fivetran or equivalent)
Hands-on experience with a data transformation framework (e.g., dbt or equivalent)
Strong SQL skills: advanced querying, optimization, and data modeling
Strong hands-on experience working with external APIs, including authentication, rate limits, pagination, and error handling
Ability to design, build, and maintain custom API-based data ingestion pipelines in Python
Hands-on experience with Python for data engineering tasks
Practical experience operating workflow orchestration tools such as Airflow
Ownership and administration of cloud data environments such as AWS or Azure, including account-level responsibility for data workloads
A strong sense of accountability – comfortable being the go-to person for your data domains and available to respond when issues arise outside of regular hours
Genuine curiosity about developments in the AI and data space – someone who actively follows trends, is eager to experiment, and brings new ideas to the table
This position is open to all candidates.
