Senior Data Platform Engineer — Hybrid | Scalable Pipelines

Thomson Reuters; New York (NY); Hybrid; USD 136,000 - 253,000; Full time

Benefits offered by this job

Hybrid Work Model

Flex My Way policies

Mental Health Days

Headspace app access

401k with company match

Tuition reimbursement

Volunteer days off

Job summary

Thomson Reuters seeks a Senior Data Platform Engineer in New York with 7+ years in software engineering, focusing on data platforms and backend infra. You will design, build, and maintain scalable pipelines and services for large volumes of legal and financial data.

Responsibilities include governance, privacy controls, and GDPR compliance, plus mentoring engineers and collaborating with ML teams. Hybrid work, strong growth and industry-leading benefits offered.

Qualifications

• Seven or more years of software engineering experience, incl. at least four years in data platforms/back-end infra.
• Experience with distributed systems, data warehousing, or large-scale data tech (Hadoop/Spark/Snowflake).
• Proficiency in at least one systems language (Python/Java/C++/Go) and scalable API design.

Responsibilities

• Design and optimize pipelines for ingesting, transforming, and distributing large-scale document data.
• Build and maintain reliable backend services for storage, retrieval, and processing.
• Implement data governance, privacy controls, audit trails, and regulatory compliance (GDPR).
• Lead database migrations, improve schema design and query performance.
• Partner with ML/AI teams to support model training and inference at scale.

Skills

Distributed systems

SQL/NoSQL databases

Cloud platforms (AWS, Azure, GCP)

Programming languages: Python/Java/C++

Data governance and privacy

Tools

Hadoop

Spark

Snowflake

Job description

Thomson Reuters seeks a Senior Data Platform Engineer in New York with 7+ years in software engineering, focusing on data platforms and backend infra. You will design, build, and maintain scalable pipelines and services for large volumes of legal and financial data.

Responsibilities include governance, privacy controls, and GDPR compliance, plus mentoring engineers and collaborating with ML teams. Hybrid work, strong growth and industry-leading benefits offered.