Manager, Data Engineer

Requisitos e responsabilidades

Conteúdo da vaga extraído em seções para revisão mais rápida.

Details

Lead delivery of high-quality data solutions by partnering with stakeholders and coachingdataengineers.
Own end-to-end data engineering delivery across the project lifecycle.
Build strong partnerships across the organization to align priorities anddeliverdata-related goals.
Design clear, analytics-ready data structures byanticipatingdownstream analytical needs.
Evaluate and adoptnew technologiesand data sources to improve capability and efficiency.
Automate data ingestion and integration to reliably connect internal and external data sources.
Document data sources, definitions, and technical solutions to support transparency and reuse.
Reinforce strong delivery hygiene (version control, code review, automated testing, CI/CD, and operational readiness/monitoring).
Apply agentic, AI-assisted coding practices to accelerate delivery whilemaintainingappropriate controls.
Build agent-ready data assets, including semantic layer components (ontology, taxonomy, domain models) and governed access.
Provide retrieval-ready context (RAG pipelines, vector stores, knowledge bases) when needed.
Strong programmingexpertisein Python and SQL, including data engineering frameworks, large-scale data manipulation, and governed AI-assisted development practices
Apache Sparkproficiency(PySparkpreferred) and experience with distributed data processing, including building scalable pipelines andoptimizingperformance for large-scale datasets
Cloud data platformproficiency(Snowflake, Databricks, Azure ecosystem fundamentals)
Data warehousing and modeling fundamentals (schema design, conformed definitions, performance optimization)
Data quality and observability practices (testing, reconciliation, monitoring)
Insurance data modelingforanalytics and actuarial-ready data structures
MLOpsfamiliarity supporting operationalized analytics and models
Semantic modeling skills (business definitions, metrics, ontology/taxonomy/domain models)
Business definition standardization for reuse across BI and AI use cases
Self-directed execution and ownership in a distributed environment, combined with strong cross-functional collaboration, stakeholder partnership, and team building
Strong problem-solving and critical thinking skills, including the ability to decompose complex challenges
Clear communication across technical and business audiences, with the ability to adapt effectively in ambiguous and evolving environments
6+years’ experienceofhands-on development in Python and distributed processing environments (e.g., Spark)
2–3+ years of technical leadership or project delivery ownership experience
Hands-on Databricks experience highly preferred
College degree in Computer Science, Engineering, Statistics, Mathematics, Actuarial Science, Data Analytics, or equivalent.

$100,500 - $174,000/year

Total individual compensation (base salary, short & long-term incentives) offered will take into account a number of factors including but not limited to geographic location, scope & responsibilities of the role, qualifications, talent availability & specialization as well as business needs. The above pay range may be modified in the future.
Arch is committed to helping employees succeed through our comprehensive benefits package that includes multiple medical plans plus dental, vision and prescription drug coverage; a competitive 401k with generous matching; PTO beginning at 20 days per year; up to 12 paid company holidays per year plus 2 paid days of Volunteer Time Offer; basic Life and AD&D Insurance as well as Short and Long-Term Disability; Paid Parental Leave of up to 10 weeks; Student Loan Assistance and Tuition Reimbursement, Backup Child and Elder Care; and more. Click here to learn more on available benefits.

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