Staff Data Engineer
Bags · New York
The role
This role involves architecting, building, and scaling real-time data infrastructure for a crypto social finance platform. The engineer will work on high-throughput pipelines, analytics systems, and storage solutions, taking full ownership from concept to production. The environment is fast-paced, in-person, and demands high performance and immediate impact.
- Location
- New York
- Work mode
- Onsite
- Level
- Staff
What we know that the posting doesn’t say
- Seen 1 day agostill listed on the employer’s careers page
- Posted 22 days agothe first time we saw it
About Bags
Bags.fm is a development company that builds and operates the technology stack for bags.fm, a launchpad for new projects and ideas, described as the world's largest crypto social network.
What you would do
- Architect and ship high-performance data solutions quickly
- Work across streaming pipelines, data modelling, and analytics databases
- Rapidly prototype and iterate on new data features
- Solve complex challenges around data consistency, performance, and scale
- Collaborate with engineering and product leaders
- Take full ownership from concept to production and maintenance
Must have
- Experience building and scaling data platforms
- Deep expertise in data engineering and distributed systems
- Fluent in SQL and Python
- Hands-on experience with Spark, Kafka, Airflow, dbt, ClickHouse, BigQuery, or Snowflake
- Designed and operated reliable batch and real-time data pipelines
- Experience modeling complex datasets for analytics or machine learning
- Comfortable making architectural decisions
- Can independently drive large technical initiatives
- Mentors other engineers through technical leadership and code reviews
- Communicates complex technical concepts clearly
- Motivated by ownership and fast-moving environments
Nice to have
- Experience with cryptocurrency and blockchain data
- Strong data visualisation skills with Omni or Looker
- Experience with event tracking data
- Advanced knowledge of statistical methods and causal inference
- Experience building pipelines with Dagster or DBT
- Familiarity with Machine Learning methods and applications
- Experience in consumer tech products or fintech
What you get
- Unmatched ownership and autonomy
- Exposure to systems at the edge of crypto scale
- Ability to ship fast and see real-world impact
Key skills
- sql
- python
- spark
- kafka
- airflow
- dbt
- clickhouse
- bigquery
- snowflake
- dagster
- looker
- omni
- machine learning
- statistics
- causal inference
- data pipelines
- distributed systems
- cloud infrastructure
- data modeling
- real-time processing
WHO ARE WE Bags.fm is the development company that builds and operates the entire technology stack behind bags.fm https://bags.fm, the leading launchpad for new projects and ideas. The systems are low latency, high throughput, live under constant load, and break if you get them wrong. WHAT YO…
Extracted from the employer’s posting. Read it in full on Bags’s careers pageApply without filling the form
Approve this role and the application is completed for you, including a résumé tailored to it. You get a confirmation when it lands, and a credit is only spent when a submission is confirmed.
Other roles at Bags
- Staff Full Stack EngineerNew York
- Staff Frontend EngineerNew York
- Senior Staff Full Stack EngineerNew York
- Junior Full Stack EngineerNew York