Senior Data Engineer

Accelerant; New York (NY); On-site; USD 130,000 - 190,000; Full time

Job summary

Accelerant is building a greenfield data enrichment capability to fuse third-party datasets with internal data and AI insights for underwriting, claims, and analytics. As Senior Data Engineer, you will drive production pipelines, matching logic, APIs, and enrichment services that directly impact risk decisions.

You will evaluate vendors, design ELT workflows, implement data governance, and collaborate across Analytics Engineering, Data Science, and Actuarial teams to deliver reliable data

Qualifications

• Experience building and operating production data pipelines using API and file-based integrations.
• Strong SQL and Python skills with ability to write maintainable ETL/ELT.
• Familiarity with modern cloud data platforms and tooling (dbt, Snowflake).
• Hands-on with entity matching, data quality, metadata lineage, and governance.

Responsibilities

• Evaluate and onboard new data vendors, validating data quality and coverage.
• Build and operate scalable ingestion pipelines for APIs and bulk file feeds.
• Design ELT workflows using Python, SQL, dbt, Snowflake (or equivalent).
• Develop entity resolution and record-linkage across datasets.
• Create APIs and services to share enriched data across teams.
• Implement data governance controls including lineage and permissions.
• Own geocoding, address standardisation, monitoring, and alerting.
• Build confidence-scoring and multi-source data resolution frameworks.
• Partner with Analytics Eng, Data Science, Actuarial, and vendors to deliver data products.

Skills

SQL

Python

TypeScript

API dev

Data pipelines

Entity matching

Data quality

Metadata governance

LLM data

Education

BS/BA in CS or related

Tools

dbt

Snowflake

Job description

At Accelerant, better risk decisions come from better data. We're building a greenfield data enrichment capability that combines third-party datasets, internal products, AI-generated insights, and platform services into a trusted source of truth for underwriting, claims, exposure management, and data science.

As a Senior Data Engineer, you'll own the journey from evaluating new data vendors through to production-ready pipelines, matching logic, APIs, and enrichment services. This is a highly visible role where the quality of your work directly impacts business-critical risk decisions.

What You'll Be Doing

• Evaluate and onboard new data vendors, validating data quality, coverage, match rates, and operational fit.
• Build and operate scalable ingestion pipelines for APIs and bulk file feeds.
• Design ELT workflows using technologies such as Python, SQL, dbt, Snowflake (or equivalent).
• Develop entity resolution and record-linkage capabilities that connect messy external datasets to internal policy and claims data.
• Create APIs and services that make enriched data available across underwriting, analytics, data science, and platform teams.
• Implement data governance controls including lineage, source attribution, permissions, and usage restrictions.
• Own geocoding, address standardisation, monitoring, alerting, and operational support.
• Build confidence-scoring and multi-source data resolution frameworks to improve data quality and trust.
• Partner closely with Analytics Engineering, Data Science, Actuarial, and external vendors to deliver valuable data products.

What We're Looking For

• Proven experience building and operating production data pipelines using both API and file-based integrations.
• Strong experience with SQL and Python and/or TypeScript.
• Experience with dbt, Snowflake, or modern cloud data platforms.
• Practical expertise in entity matching, record linkage, and data quality management.
• Experience building and supporting production APIs and services.
• Strong understanding of metadata, lineage, governance, permissions, and data usage controls.
• Comfortable taking ownership of ambiguous problems and turning them into reliable data products.
• Experience using AI-assisted development practices or working with LLM-generated data.