Director, ETL & Data Engineering (Hybrid)

Career Techniques; New York (NY); Hybrid; USD 180,000 - 240,000; Full time

Job summary

Career Techniques is seeking a Director of ETL and Data Engineering to lead a team in building enterprise data integration platforms and ETL pipelines in New York. You will ensure data integrity, security, and availability while enabling analytics and automated business processes.

You will architect scalable data platforms, mentor engineers, oversee testing and governance, and collaborate with stakeholders to define data processes.

Qualifications

• 7+ years professional software development experience.
• 3+ years in a technical leadership or senior engineering role.
• 5+ years hands-on ETL, shell scripting, and process orchestration.
• Expert knowledge of database and data warehouse design principles.
• Experience with Scrum and Agile methodologies.
• Excellent communication with stakeholders.

Responsibilities

• Lead a team to deliver scalable data integration solutions.
• Architect ETL pipelines and data platforms.
• Provide hands-on technical leadership and code reviews.
• Oversee security, data governance, and quality.
• Drive agile development and testing strategies.
• Collaborate with analysts and business owners on requirements.
• Maintain in-person on-site presence per hybrid schedule.

Skills

ETL pipelines

Data warehousing

Data modeling

Agile leadership

Programming languages

Data governance

Team leadership

Security awareness

Education

Bachelor’s or Master’s degree in software engineering or related field

Tools

Airflow

SQL

Python

Shell scripting

Job description

Career Techniques is seeking a Director of ETL and Data Engineering to lead a team in building enterprise data integration platforms and ETL pipelines in New York. You will ensure data integrity, security, and availability while enabling analytics and automated business processes.

You will architect scalable data platforms, mentor engineers, oversee testing and governance, and collaborate with stakeholders to define data processes.