Data Operations Engineer: Pipelines & Data Quality

Doist; New York (NY); On-site; USD 101,500 - 122,000; Full time

Benefits offered by this job

401(k) match

Tuition reimbursement

Paid parental leave

Calm app / wellbeing

Job summary

GLG is seeking a Data Operations Engineer to build, run, and maintain data pipelines and integrations that power GLG's platforms. You will write and optimize SQL, use Python for data manipulation, and collaborate with engineers, analysts, and stakeholders to ensure data quality and reliable delivery.

Ideal candidates have 2–3 years in data operations or data engineering, a solid understanding of relational databases, and familiarity with AI tooling (Claude, Copilot, Open code).

Qualifications

• 2–3 years of experience in a data operations, data engineering, or similar data-focused role.
• Strong SQL and a solid understanding of relational databases.
• Proficiency in Python for data manipulation and automation.
• Solid grasp of data fundamentals — modeling, transformation, data quality.
• Inquisitive, generalist mindset — eager to learn systems end-to-end.
• Experience using Claude, Copilot, OpenAI tools and other AI toolsets.

Responsibilities

• Build, run, and maintain data pipelines, imports, and integrations that feed GLG's platforms and reporting.
• Write and optimize SQL to move, transform, and validate data across sources.
• Monitor scheduled jobs, triage failures, and resolve data-quality and data-accuracy issues.
• Collaborate with cross-functional teams to turn business needs into reliable data deliverables.
• Write clean, maintainable code and queries.
• Contribute to runbooks, documentation, and best practices.

Skills

SQL

Python

Data modeling

Data quality

AI tooling

Problem solving

Tools

Snowflake

Airflow

OpenSearch

AWS

CI/CD

DevOps

Job description

GLG is seeking a Data Operations Engineer to build, run, and maintain data pipelines and integrations that power GLG's platforms. You will write and optimize SQL, use Python for data manipulation, and collaborate with engineers, analysts, and stakeholders to ensure data quality and reliable delivery.

Ideal candidates have 2–3 years in data operations or data engineering, a solid understanding of relational databases, and familiarity with AI tooling (Claude, Copilot, Open code).