Data Engineer - Scalable Pipelines & AI Data Platforms

Jobtailor; New York (NY); On-site; USD 140,000 - 190,000; Full time

Job summary

SignalFire is seeking a data engineer to design, build, and maintain scalable batch and real-time data pipelines. You will develop robust data models, transformation workflows, and shared datasets for analytics and operations across product, customer, financial, and third-party systems.

Join to build cloud-based data warehouses, lakehouses, and data platforms, ensuring data quality, observability, and governance while collaborating with analytics, product, engineering, and business teams to

Qualifications

• 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.
• LinkedIn URL required
• Resume/CV required; PDF format preferred
• Current or preferred working location required on the application
• Must provide consent for SignalFire to collect, store, process, and potentially share submitted information with portfolio companies
• Must consent to communications from SignalFire

Responsibilities

• 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
• Develop training, feature, and inference data pipelines supporting machine learning and AI applications
• Improve the performance, scalability, and cost efficiency of data infrastructure
• Build self-service tools and frameworks that make data easier to discover and use
• 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
• Submit an application to SignalFire’s Talent Ecosystem
• Work with SignalFire talent partners or portfolio-company leaders if a potential match is identified
• Maintain profile consideration for future Data Engineering roles across the portfolio

Skills

Python

Java

Scala

SQL

Data Modeling

ETL/ELT

Cloud Platforms

Tools

AWS

GCP

Azure

Snowflake

BigQuery

Redshift

Databricks

Job description

SignalFire is seeking a data engineer to design, build, and maintain scalable batch and real-time data pipelines. You will develop robust data models, transformation workflows, and shared datasets for analytics and operations across product, customer, financial, and third-party systems.

Join to build cloud-based data warehouses, lakehouses, and data platforms, ensuring data quality, observability, and governance while collaborating with analytics, product, engineering, and business teams to