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Remote – Europe · European Union
Actively hiring, first seen by us 1 day agoLocation type: RemoteFrom the employer’s posting
Employment type: Full-timeFrom the employer’s posting
Department: Engineering & Product › Data & AIFrom the employer’s posting
Build a reusable Python ingestion framework to speed up each new customer integration
Replace the legacy Java ETL with the new framework
Keep PostgreSQL and Snowflake in sync with real-time streaming and change data capture
Use LLMs to map customer schemas and reduce manual integration work
Own pipelines in production, including monitoring, data quality, recovery and secure data handling
build a Python ingestion framework that turns the next customer integration into something we can reuse, improve and scale
replaces our legacy Java ETL
Keep PostgreSQL and Snowflake in sync through reliable real-time streaming and change data capture pipelines
Make onboarding smarter by using LLMs to map customer schemas and reduce manual integration work
Own your pipelines in production, from deployment and monitoring to data quality, recovery and secure handling of customer data
4+ years in data engineering, building Python and SQL pipelines for complex integrations: unfamiliar sources, inconsistent schemas and incomplete documentation.
Experience with dbt and DuckDB.
Hands-on experience with streaming and CDC, including schema changes, backfills and recovery after failures.
Experience managing infrastructure with Terraform.
Familiarity with cross-warehouse data sharing or LLM-assisted data integration.
Nevis is building the world’s first AI wealth management platform.
In the employer’s words · Read in context · Company website ↗
Actively hiringFirst seen by us 1 day ago, still listed, and not a repost of an earlier posting.
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Day 1
Early. Similar jobs usually come down between day 6 and day 54.
From 11,470 similar postings that came down. Coming down is not always a hire.
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What You’ll Do - Build a reusable Python ingestion framework that makes each new customer integration faster and replaces our legacy Java ETL. - Keep PostgreSQL and Snowflake in sync through reliable real-time streaming and change data capture pipelines.
The Role Every firm joining Nevis brings its own systems, schemas and data quirks. Your job is to make that complexity easier to handle: build a Python ingestion framework that turns the next customer integration into something we can reuse, improve and scale. You’ll also build the real-time pipelines connecting PostgreSQL and Snowflake, keeping data flowing reliably as Nevis grows. You’ll join our Data & AI Platform team, with plenty of room to shape how we build. There’s existing code to improve, new infrastructure to design and an opportunity to use LLMs to make schema mapping and onboarding less manual. If you like understanding a messy problem, making practical decisions and seeing your work run in production, there’s a lot here to get stuck into.
Who You Are - 4+ years in data engineering, building Python and SQL pipelines for complex integrations: unfamiliar sources, inconsistent schemas and incomplete documentation. - Hands-on experience with streaming and CDC, including schema changes, backfills and recovery after failures.
- Hands-on experience with streaming and CDC, including schema changes, backfills and recovery after failures. - Production experience with PostgreSQL, Snowflake, cloud infrastructure (ideally AWS) and Airflow or similar tools. You own deployment, monitoring and troubleshooting. - You use AI tools daily, with concrete examples of integrating them into your workflow to automate tasks and improve how you build
Nice to Have - Experience with dbt and DuckDB. - Experience managing infrastructure with Terraform.
- Build a reusable Python ingestion framework that makes each new customer integration faster and replaces our legacy Java ETL. - Keep PostgreSQL and Snowflake in sync through reliable real-time streaming and change data capture pipelines. - Make onboarding smarter by using LLMs to map customer schemas and reduce manual integration work.
- Experience with dbt and DuckDB. - Experience managing infrastructure with Terraform. - Familiarity with cross-warehouse data sharing or LLM-assisted data integration.
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New Data Engineer postings at the employers we follow are up 8% over the last 5 weeks compared with the 5 before.
Each bar is one week of new postings. The darkest bars are the last 5 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under Data Engineer, by the work the posting describes.
Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.
Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.
An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.
The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.
Nevis is building the world’s first AI wealth management platform. We are building the system financial advisors will run on for the next decade. Our AI completes work, automates workflows end to end, and frees advisors to spend more time with clients. In the future, every wealth management firm will run on Nevis.
Nevis was founded by an exceptional team of ex-Revolut executives and has raised $110 million in just two years, including a $70 million Series B led by EQT Ventures & Growth, backed by world-leading investors including Sequoia Capital, ICONIQ, and Ribbit.
Every firm joining Nevis brings its own systems, schemas and data quirks. Your job is to make that complexity easier to handle: build a Python ingestion framework that turns the next customer integration into something we can reuse, improve and scale. You’ll also build the real-time pipelines connecting PostgreSQL and Snowflake, keeping data flowing reliably as Nevis grows.
You’ll join our Data & AI Platform team, with plenty of room to shape how we build. There’s existing code to improve, new infrastructure to design and an opportunity to use LLMs to make schema mapping and onboarding less manual. If you like understanding a messy problem, making practical decisions and seeing your work run in production, there’s a lot here to get stuck into.
Build a reusable Python ingestion framework that makes each new customer integration faster and replaces our legacy Java ETL.
Keep PostgreSQL and Snowflake in sync through reliable real-time streaming and change data capture pipelines.
Make onboarding smarter by using LLMs to map customer schemas and reduce manual integration work.
Own your pipelines in production, from deployment and monitoring to data quality, recovery and secure handling of customer data.
4+ years in data engineering, building Python and SQL pipelines for complex integrations: unfamiliar sources, inconsistent schemas and incomplete documentation.
Hands-on experience with streaming and CDC, including schema changes, backfills and recovery after failures.
Production experience with PostgreSQL, Snowflake, cloud infrastructure (ideally AWS) and Airflow or similar tools. You own deployment, monitoring and troubleshooting.
You use AI tools daily, with concrete examples of integrating them into your workflow to automate tasks and improve how you build
Experience with dbt and DuckDB.
Experience managing infrastructure with Terraform.
Familiarity with cross-warehouse data sharing or LLM-assisted data integration.
Work alongside a high-calibre founding team backed by some of the best investors in the world.
A fast-paced, high-growth environment with the opportunity to shape how the business operates.
Be part of a mission-driven company transforming the wealth management industry with huge potential for global impact.
25 days’ annual leave.
Private medical insurance.
Competitive salary and benefits package, including company equity.
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European Union
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