Data Engineer

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🔥 39 minutes ago

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SignalFire

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2012

🏥 Healthcare

💼 Consulting

📦 Logistics

Healthcare • Consulting • Logistics

SignalFire is a venture capital firm built on technology and data, dedicated to supporting growth for early-stage companies through advanced AI tools and seasoned sector expertise. They focus on providing unparalleled support to their portfolio companies, combining in-house AI capabilities with tailored advisory programs across multiple sectors such as healthcare, fintech, cybersecurity, and more.

📋 Description

• 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

🎯 Requirements

• 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

🏖️ Benefits

• 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