This global financial analytics organization is known for its long-standing credibility, industry influence, and deep technical rigor. It has earned recognition for its stability, integrity, and the critical role its data plays in informing decisions across the insurance and financial sectors.

The company is hiring a Sr. Data Engineer to help build, optimize, and scale its modern data ecosystem. This position supports a high-visibility internal initiative and plays a key role in strengthening the organization’s analytics platform. It’s an excellent opportunity for someone who wants to make a visible impact in a mature, data-driven environment.

This is a full-time, direct-hire role based in the Bedminster, NJ area, operating in a hybrid environment.

The Role You’ll Play

You’ll be part of the core data engineering group responsible for building scalable, reliable data systems used across the organization. This includes leading efforts around data pipelines, metadata-driven architecture, governance, cloud integration, automation, and performance optimization. This team supports high-stakes work that feeds into major internal decision-making processes.

• Build and support high-performance data systems, including databases, APIs, and integration pipelines.

• Implement metadata-driven architecture and infrastructure-as-code approaches.

• Promote and enforce engineering best practices (code review, testing, CI/CD).

• Establish and support data governance frameworks.

• Tune and optimize ETL/ELT processes, queries, and code.

• Leverage Azure and Databricks to enhance data architecture.

• Implement automated data quality checks and issue-resolution processes.

• Produce documentation for architecture, standards, and best practices.

• Provide technical leadership while staying hands-on in coding and design.

• Identify opportunities for automation and operational efficiency.

Background Profile

You’re a seasoned Data Engineer with deep hands-on technical skills, strong Python experience, and a track record of building and maintaining complex data pipelines. You bring a problem-solving mindset and enjoy contributing code, designs, and tools that improve system reliability and performance.

• 7+ years in Data Engineering, Data Architecture, or Database Development

• 7+ years coding in Python, Scala, Java, Rust, or similar

• 7+ years Oracle OLTP design and development

• 7+ years building ETL/ELT pipelines (Spark, Airflow, dbt, etc.)

• 7+ years developing APIs (REST, SOAP, RPC, GraphQL)

• 7+ years OLAP/data warehouse design (Kimball, Inmon, Data Vault)

• 5+ years NoSQL (MongoDB or similar)

• 5+ years message brokers (Kafka, RabbitMQ, Red Hat AMQ)

• 5+ years Azure or AWS cloud experience

• Working knowledge of CI/CD (Jenkins, Ansible, Chef, Puppet)

• Working knowledge of containers (Docker, Kubernetes)

Preferred/Nice to Have:

• Databricks

• PowerBI, Tableau, Cognos

• Redis/Memcache

• Elasticsearch/Solr

• ERwin / ERStudio / SqlDBM

• Collibra / Alation

• Informatica / Ataccama / TIBCO MDM