Senior Data Engineer
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Job Description
Senior Data Engineer delivering modern data solutions at Carrier, focused on data pipelines and lakehouse architectures. Collaborating with cross-functional teams to support analytics and reporting.
Responsibilities:
- Design, build, and optimize data ingestion, transformation, and delivery pipelines that support batch, micro‑batch, and streaming workloads.
- Develop ETL/ELT workflows that integrate data from enterprise systems, operational platforms, external sources, and commercial applications.
- Implement scalable data processing patterns that support open lakehouse architectures and medallion‑layered data products.
- Ensure pipelines are reliable, maintainable, cost‑efficient, and aligned with enterprise engineering standards.
- Design data models that support analytics, reporting, and data product consumption across raw, refined, and curated layers.
- Apply medallion architecture principles to ensure data quality, reusability, and consistency across domains.
- Contribute to architectural decisions that balance performance, scalability, governance, and operational simplicity.
- Support integration of ERP and enterprise systems, ensuring data consistency and alignment with business processes.
- Implement data quality checks, validation rules, and monitoring frameworks to ensure accuracy and reliability.
- Apply foundational data governance practices including lineage, metadata management, cataloging, and access controls.
- Collaborate with governance and data product teams to ensure compliance with enterprise standards and regulatory requirements.
- Partner with CSA teams, solution architects, and data product leads to translate business requirements into technical specifications.
- Work closely with customer engineering and analytics teams to support onboarding, adoption, and operationalization of delivered pipelines.
- Participate in Agile delivery processes, providing technical input on sizing, sequencing, and implementation planning.
- Communicate technical concepts clearly to both technical and non‑technical stakeholders.
Requirements:
- Bachelor’s degree.
- 5+ years of experience in data engineering.
- 5+ years of experience in open lakehouse architecture in Azure, GCP, AWS and/or Snowflake.
- 5+ years of experience creating automated data pipelines and performing data modeling.
- 5+ years of experience writing SQL, Python, and modern ETL/ELT frameworks.
Benefits:
- Health Care Benefits : Medical, Dental, Vision
- Wellness incentives
- Retirement Benefits
- Time off and Leave : Paid vacation days, up to 15 days; paid sick days, up to 5 days; paid personal leave, up to 5 days; paid holidays, up to 13 days; birth and adoption leave; parental leave; family and medical leave; bereavement leave; jury duty leave; military leave; purchased vacation
- Disability : Short-term and long-term disability
- Life Insurance and Accidental Death and Dismemberment
- Tax-Advantaged Accounts: Health Savings Account; Health Care Spending Account; Dependent Care Spending Account
- Tuition Assistance
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