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The Senior Data Engineer enables the delivery of modern, scalable data solutions across commercial, operational, and enterprise domains within CSA engagements. The role focuses on designing and building robust data pipelines, integrating diverse data sources, and supporting open lake‑house and medallion‑layered architectures. This engineer works closely with solution architects, data product leads, and customer teams to translate requirements into production‑ready data assets that power analytics, reporting, and data products across the organization.
Job Responsibility:
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
Implement data quality checks, validation rules, and monitoring frameworks
Apply foundational data governance practices including lineage, metadata management, cataloging, and access controls
Collaborate with governance and data product teams
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
Participate in Agile delivery processes
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
Nice to have:
Bachelor's of Science in Computer Science, Engineering, or technical related field
Strong experience designing and building data pipelines, transformations, and data models
Proficiency in SQL, Python, and modern ETL/ELT frameworks
Experience implementing open lakehouse architectures and medallion‑layered data products
Strong understanding of data integration patterns, orchestration, and distributed data processing
Experience working with ERP and enterprise systems
Experience working in customer‑facing delivery environments
Ability to work across cross‑functional engineering, product, and business teams
Strong communication skills
Experience working within Agile delivery models
Experience with cloud platforms and modern data ecosystems
Data replication tools for enterprise systems
Background supporting commercial, operational, or enterprise analytics use cases
Familiarity with CI/CD, infrastructure‑as‑code, and modern DevOps practices
Experience mentoring junior and early career engineers
Knowledge of manufacturing, logistics, and supply chain domain
Experience working with ERP and CRM platforms such as Salesforce
What we offer:
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