
11 - 50 employés
Fondée en 2012
🏥 Santé
💼 Conseil
📦 Logistique
Healthcare • Consulting • Logistics
SignalFire est une société de capital-risque construite sur la technologie et les données, dédiée à soutenir la croissance des entreprises en phase de démarrage grâce à des outils d'IA avancés et une expertise sectorielle éprouvée. Ils se concentrent sur l'apport d'un soutien sans égal à leurs entreprises en portefeuille, combinant des capacités d'IA internes avec des programmes de conseil sur-mesure dans plusieurs secteurs tels que la santé, la fintech, la cybersécurité, et plus encore.
🕒 il y a 1 jour
🗣️🇺🇸🇬🇧 Anglais requis
Airflow
Amazon Redshift
AWS
Azure
BigQuery
Cloud
Distributed Systems
Docker
DynamoDB
ETL
Google Cloud Platform
Java
Kafka
Kubernetes
MongoDB
MySQL
Postgres
Python
Scala
Spark
SQL
Terraform
Go
Améliorez vos chances d'obtenir un entretien en vérifiant votre score de CV avant de postuler.

11 - 50 employés
Fondée en 2012
🏥 Santé
💼 Conseil
📦 Logistique
Healthcare • Consulting • Logistics
SignalFire est une société de capital-risque construite sur la technologie et les données, dédiée à soutenir la croissance des entreprises en phase de démarrage grâce à des outils d'IA avancés et une expertise sectorielle éprouvée. Ils se concentrent sur l'apport d'un soutien sans égal à leurs entreprises en portefeuille, combinant des capacités d'IA internes avec des programmes de conseil sur-mesure dans plusieurs secteurs tels que la santé, la fintech, la cybersécurité, et plus encore.
• Connect exceptional Data Engineers with VC-backed startups actively hiring data engineering talent • Design, build, and maintain scalable batch and real-time data pipelines • Develop reliable data models, transformation workflows, and shared datasets for analytics and operational use cases • Build and manage cloud-based data warehouses, lakehouses, and data platforms • Integrate data from product, customer, financial, and third-party systems • Establish standards for data quality, testing, lineage, observability, and documentation • Partner with analytics, product, engineering, and business teams to understand data requirements • Support machine learning and AI applications with training, feature, and inference data pipelines • Improve the performance, scalability, and cost efficiency of data infrastructure • Build self-service tools and frameworks to improve data discovery and usability • Implement access controls, privacy safeguards, and data-governance practices • Troubleshoot pipeline failures, data-quality issues, and performance bottlenecks • Help define broader data architecture and technical roadmaps • SignalFire reviews applications on an ongoing basis and may connect candidates with portfolio-company talent partners or leaders
• 3+ years of experience in data engineering, software engineering, analytics engineering, or a related technical role • Strong programming skills in Python, Java, Scala, or a similar language • Advanced proficiency in SQL and experience designing scalable data models • Experience building and maintaining production ETL or ELT pipelines • Familiarity with cloud platforms such as AWS, GCP, or Azure • Experience with modern data warehouses or lakehouse platforms such as Snowflake, BigQuery, Redshift, or Databricks • Knowledge of workflow orchestration, transformation, and data-quality tooling • Understanding of distributed systems, data storage formats, and batch or streaming architectures • Ability to collaborate with technical and non-technical stakeholders to translate business needs into data solutions • Strong judgment around reliability, scalability, governance, and infrastructure tradeoffs • Experience in venture-backed startups or rapidly scaling technology companies may be preferred • Technologies mentioned include Go, Delta Lake, Airflow, Dagster, Prefect, dbt, Fivetran, Airbyte, Kafka, Spark, Flink, Kinesis, Pub/Sub, Docker, Kubernetes, Terraform, Great Expectations, Monte Carlo, Soda, DataHub, OpenLineage, PostgreSQL, MySQL, DynamoDB, MongoDB, and S3
• Profile shared with SignalFire portfolio companies for visibility into exclusive early-stage opportunities • Profile kept on file for future Data Engineering roles across the portfolio • Potential access to opportunities that may not be publicly listed
Postuler Maintenant🕒 il y a 2 jours
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