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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in building and managing data pipelines using Python and SQL, with a focus on real-time streaming and change data capture. Proficient in deploying and monitoring data infrastructure in production environments, ensuring data quality and secure handling.
Highest-signal resume keywords
Python Ingestion Framework DevelopmentReal-Time Streaming and Change Data CapturePostgreSQL and Snowflake ManagementDeployment and Monitoring of Data PipelinesInfrastructure Management with Terraform
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
PythonSQLStreaming Data PipelinesChange Data CapturePostgreSQLSnowflakeAirflowDbtDuckDBTerraform
Tools & Technologies
AWSAI Tools
Industry Keywords
Data EngineeringData IntegrationData QualityInfrastructure ManagementCross-Warehouse Data Sharing
Tech Stack
Tools & technologiesAirflowAWSCloudETLJavaPostgresPythonSnowflakeSQLTerraform
About the role
Key responsibilities & impact- Build a reusable Python ingestion framework to accelerate customer integrations and replace the legacy Java ETL
- Keep PostgreSQL and Snowflake synchronized through reliable real-time streaming and change data capture pipelines
- Use LLMs to map customer schemas and reduce manual integration work
- Own data pipelines in production, including deployment, monitoring, data quality, recovery and secure handling of customer data
- Improve existing code and design new infrastructure as part of the Data & AI Platform team
Requirements
What you’ll need- 4+ years in data engineering
- Experience building Python and SQL pipelines for complex integrations involving unfamiliar sources, inconsistent schemas and incomplete documentation
- Hands-on experience with streaming and change data capture, including schema changes, backfills and recovery after failures
- Production experience with PostgreSQL, Snowflake, cloud infrastructure, ideally AWS, and Airflow or similar tools
- Experience owning deployment, monitoring and troubleshooting
- Daily use of AI tools, with concrete examples of integrating them into workflows to automate tasks and improve development
- Experience with dbt and DuckDB
- Experience managing infrastructure with Terraform
- Familiarity with cross-warehouse data sharing or LLM-assisted data integration
- Right to work in the location applied for
Benefits
Comp & perks- 25 days’ annual leave
- Private medical insurance
- Competitive salary and benefits package
- Company equity
- Fast-paced, high-growth environment with the opportunity to shape how the business operates
- Opportunity to work alongside a high-calibre founding team backed by leading investors
- Opportunity to contribute to a mission-driven company transforming the wealth management industry
- Opportunity to use LLMs to improve schema mapping and customer onboarding