Position Summary:
The Senior Data Engineer designs, builds, and maintains scalable data pipelines, cloud data architectures, and ETL processes that enable business analytics and insights. Operating with limited supervision, this role partners with data analysts, data scientists, and business stakeholders to translate requirements into secure, efficient, and reliable data solutions.
Key Responsibilities:
Design and manage ETL/ELT pipelines and data warehouse architectures in Azure, GCP, or AWS.
Implement DataOps/DevOps practices, automation, and version control (GitHub/GitLab).
Ensure compliance with data security, privacy, and governance standards.
Create and maintain data dictionaries, catalogs, and lineage documentation.
Partner cross-functionally to align technical delivery with business needs.
Contribute to the design and enhancement of enterprise data architecture frameworks (Data Vault 2.0, Medallion).
Apply financial acumen to assess project value and cost efficiency.
Communicate technical findings clearly to stakeholders.
Qualifications:
Bachelor’s degree in Computer Science, Data Analytics, Mathematics, Statistics, or related field required.
2+ years of experience in data engineering or data architecture; Master’s preferred.
Proficient in SQL, Python, and/or Spark.
Skilled in ETL/ELT tools, cloud-native data platforms, and distributed computing.
Familiar with DataOps, DevOps, or SecOps frameworks.
Strong collaboration, communication, and problem-solving skills.
Knowledge & Competencies:
Object-oriented programming and data structure fundamentals.
Data architecture principles and optimization strategies.
Data security and compliance standards.
Ability to independently manage priorities and projects.