Data Pipelines & Quality Engineer

Socket.dev; Austin (TX); On-site; USD 101,500 - 122,000; Full time

Benefits offered by this job

Medical benefits

Flexible time off

Job summary

GLG is seeking a Data Operations Engineer in Austin, TX to join our Data Operations team. You will build, run, and troubleshoot data pipelines and integrations that power GLG’s platforms, writing and optimizing SQL and Python to move and validate data across sources.

The ideal candidate has 2–3 years of experience in data operations or data engineering, a solid understanding of relational databases, and a proactive, collaborative mindset.

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 a scripting language (Python preferred) for data manipulation and automation.
• Solid grasp of data fundamentals — modeling, transformation, data quality.
• An inquisitive, generalist mindset — eager to learn systems end-to-end rather than staying in one niche.

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, and efficient code and queries.
• Contribute to runbooks, documentation, and operational best practices.
• Stay curious about new tools and approaches — we’ll train you on our stack as you grow.

Skills

SQL

Python

Data pipelines

Data quality

Relational databases

Tools

Snowflake

Airflow

OpenSearch

AWS

Job description

GLG is seeking a Data Operations Engineer in Austin, TX to join our Data Operations team. You will build, run, and troubleshoot data pipelines and integrations that power GLG’s platforms, writing and optimizing SQL and Python to move and validate data across sources.

The ideal candidate has 2–3 years of experience in data operations or data engineering, a solid understanding of relational databases, and a proactive, collaborative mindset.