Senior Data Engineer

Carrier•Atlanta, GA

6d•$96,000 - $192,000

About The Position

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.

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.
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, with an emphasis on data extraction, modeling, and harmonization.
Experience working in customer‑facing delivery environments, supporting CSA or similar solution‑oriented teams.
Ability to work across cross‑functional engineering, product, and business teams.
Strong communication skills for explaining technical concepts and influencing architectural decisions.
Experience working within Agile delivery models.

Nice To Haves

Bachelor’s of Science in Computer Science, Engineering, or technical related field.
Experience with cloud platforms and modern data ecosystems, including: 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.

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.