Manager, Data Engineer

This is a fully remote position, open to applicants in New Jersey, +3 more states.

📋 Description

• Drive the delivery of top-notch data solutions by collaborating with stakeholders and mentoring data engineers.

• Take ownership of the complete data engineering delivery throughout the project lifecycle.

• Establish robust partnerships across the organization to align priorities and achieve data-related objectives.

• Create clear, analytics-ready data structures by anticipating future analytical requirements.

• Assess and integrate new technologies and data sources to enhance capability and efficiency.

• Automate data ingestion and integration processes to reliably connect both internal and external data sources.

• Document data sources, definitions, and technical solutions to promote transparency and facilitate reuse.

• Uphold strong delivery standards (version control, code review, automated testing, CI/CD, and operational readiness/monitoring).

• Implement agentic, AI-assisted coding practices to speed up delivery while ensuring appropriate controls are in place.

• Develop agent-ready data assets, including components of the semantic layer (ontology, taxonomy, domain models) and managed access.

• Provide retrieval-ready context (RAG pipelines, vector stores, knowledge bases) as required.

⛳️ Requirements

• Over 6 years of hands-on development experience in Python and distributed processing environments (e.g., Spark).

• 2–3+ years of experience in technical leadership or project delivery ownership.

• Practical experience with Databricks is highly preferred.

• Strong programming skills in Python and SQL, including expertise in data engineering frameworks, large-scale data manipulation, and governed AI-assisted development practices.

• Proficiency in Apache Spark (PySpark preferred) and experience with distributed data processing, including the creation of scalable pipelines and performance optimization for large datasets.

• Knowledge of cloud data platforms (Snowflake, Databricks, fundamentals of the Azure ecosystem).

• Understanding of data warehousing and modeling principles (schema design, conformed definitions, performance optimization).

• Familiarity with data quality and observability practices (testing, reconciliation, monitoring).

• Readiness for analytics & AI initiatives.

• Experience with insurance data modeling for analytics and actuarial-ready data structures.

• Familiarity with MLOps to support operationalized analytics and models.

• Skills in semantic modeling (business definitions, metrics, ontology/taxonomy/domain models).

• Standardization of business definitions for reuse across BI and AI applications.

🏝️ Benefits

• Multiple medical plans along with dental, vision, and prescription drug coverage.

• A competitive 401k plan with generous matching contributions.

• Paid time off starting at 20 days per year.

• Up to 12 paid company holidays annually plus 2 paid days for Volunteer Time Off.

• Basic Life and AD&D Insurance, as well as Short and Long-Term Disability coverage.

• Paid Parental Leave of up to 10 weeks.

• Student Loan Assistance and Tuition Reimbursement programs.

• Backup Child and Elder Care support.

• And more.