Lead Data Engineer Data Architect

New York City, NY - USA

Monthly Salary: Not Disclosed

Posted on: 30+ days ago

Vacancies: 1 Vacancy

Job Summary

Key Responsibilities:

Lead the data architecture and engineering strategy ensuring alignment with business and technology roadmaps.
Design and implement data models pipelines and data integration frameworks across multiple platforms.
Partner with stakeholders to translate business requirements into scalable data solutions.
Performance Optimization: Optimize data pipelines for performance scalability and reliability including query tuning and resource management within Snowflake.
Drive adoption of best practices in data engineering design patterns and modern cloud architectures.
Data Quality Assurance: Implement and monitor data validation procedures to ensure data accuracy and consistency across systems.
Collaboration and Communication: Work closely with project managers data architects and business analysts to align project milestones and deliverables with business goals.
Mentor and guide data engineering teams (onsite & offshore) to deliver high-quality outcomes.
Ensure compliance with data governance security and privacy standards.
Documentation: Create and maintain detailed documentation of data pipelines data flow diagrams and transformation logic.
Issue Resolution: Troubleshoot and resolve issues related to data pipelines including job failures and performance bottlenecks.

Required Qualifications:

Bachelors degree in Computer Science Information Technology or a related field.
8 years of experience in data engineering with a strong focus on Data Architecture Data Modelling (Conceptual Logical Physical) ELT processes and data pipeline development.
Hands-on experience with Snowflake cloud data platform including data sharing secure views and performance optimization.
Proficiency in SQL and familiarity with data integration and ETL/ELT tools.
AWS Technologies (Glue EMR)
Python for data engineering workflows
Strong understanding of data engineering design patterns
Strong problem-solving skills and the ability to work independently to meet deadlines.
Excellent communication skills for effectively interacting with technical and non-technical stakeholders.

Key Responsibilities: Lead the data architecture and engineering strategy ensuring alignment with business and technology roadmaps. Design and implement data models pipelines and data integration frameworks across multiple platforms. Partner with stakeholders to translate business requirements i...

Key Responsibilities:

Lead the data architecture and engineering strategy ensuring alignment with business and technology roadmaps.
Design and implement data models pipelines and data integration frameworks across multiple platforms.
Partner with stakeholders to translate business requirements into scalable data solutions.
Performance Optimization: Optimize data pipelines for performance scalability and reliability including query tuning and resource management within Snowflake.
Drive adoption of best practices in data engineering design patterns and modern cloud architectures.
Data Quality Assurance: Implement and monitor data validation procedures to ensure data accuracy and consistency across systems.
Collaboration and Communication: Work closely with project managers data architects and business analysts to align project milestones and deliverables with business goals.
Mentor and guide data engineering teams (onsite & offshore) to deliver high-quality outcomes.
Ensure compliance with data governance security and privacy standards.
Documentation: Create and maintain detailed documentation of data pipelines data flow diagrams and transformation logic.
Issue Resolution: Troubleshoot and resolve issues related to data pipelines including job failures and performance bottlenecks.

Required Qualifications:

Bachelors degree in Computer Science Information Technology or a related field.
8 years of experience in data engineering with a strong focus on Data Architecture Data Modelling (Conceptual Logical Physical) ELT processes and data pipeline development.
Hands-on experience with Snowflake cloud data platform including data sharing secure views and performance optimization.
Proficiency in SQL and familiarity with data integration and ETL/ELT tools.
AWS Technologies (Glue EMR)
Python for data engineering workflows
Strong understanding of data engineering design patterns
Strong problem-solving skills and the ability to work independently to meet deadlines.
Excellent communication skills for effectively interacting with technical and non-technical stakeholders.