Principal Data Engineer

Atyeti; Princeton (NJ); On-site; USD 90,000 - 120,000; Full time

Job summary

Atyeti is seeking a data engineering professional to develop and maintain scalable data pipelines and API integrations to handle growing data volume and complexity.

You will collaborate with analytics and business teams to refine data models, improve BI readiness, and ensure data quality across production systems.

Qualifications

• Experience building scalable data pipelines and API integrations.
• Proven ability to improve data models and enable data-driven decision making.
• Strong focus on data quality, lineage, and monitoring in production systems.
• Proficient in writing tests and maintaining engineering documentation.

Responsibilities

• Develops and maintains scalable data pipelines and builds out new API integrations to support continuing increases in data volume and complexity.
• Collaborates with analytics and business teams to improve data models that feed business intelligence tools, increasing data accessibility and fostering data-driven decision making across the organization.
• Implements processes and systems to monitor data quality, ensuring production data is always accurate and available for key stakeholders and business processes that depend on it.
• Writes unit/integration tests, contributes to engineering wiki, and documents work.
• Performs data analysis required to troubleshoot data related issues and assist in the resolution of data issues.
• Works closely with a team of frontend and backend engineers, product managers, and analysts.
• Defines company data assets (data models), spark, sparkSQL, and hiveSQL jobs to populate data models.
• Designs data integrations and data quality framework.
• Designs and evaluates open source and vendor tools for data lineage.
• Works closely with all business units and engineering teams to develop strategy for long term data platform architecture.

Skills

Data modeling

Data pipeline development

API integration

Data quality

Spark

SparkSQL

HiveSQL

Data analytics

Collaboration with cross-functional"

Unit testing

Tools

Spark

SparkSQL

HiveSQL

Job description

• Develops and maintains scalable data pipelines and builds out new API integrations to support continuing increases in data volume and complexity.
• Collaborates with analytics and business teams to improve data models that feed business intelligence tools, increasing data accessibility and fostering data-driven decision making across the organization.
• Implements processes and systems to monitor data quality, ensuring production data is always accurate and available for key stakeholders and business processes that depend on it.
• Writes unit/integration tests, contributes to engineering wiki, and documents work.
• Performs data analysis required to troubleshoot data related issues and assist in the resolution of data issues.
• Works closely with a team of frontend and backend engineers, product managers, and analysts.
• Defines company data assets (data models), spark, sparkSQL, and hiveSQL jobs to populate data models.
• Designs data integrations and data quality framework.
• Designs and evaluates open source and vendor tools for data lineage.
• Works closely with all business units and engineering teams to develop strategy for long term data platform architecture.