Job Description
Octave is seeking a Data Engineer to support a large-scale cloud migration from AWS to Google Cloud Platform (GCP). This individual will play a critical role in modernizing the company’s data infrastructure, ensuring seamless data movement, and building scalable pipelines in the new environment.
This is a high-impact engagement through the end of the year, with strong opportunity to transition into ongoing data engineering and integration work post-migration.
Key Responsibilities
Support the end-to-end migration of data systems from AWS to GCP
Design, build, and optimize scalable data pipelines and transformations
Work with large datasets across cloud-based data warehouses (Redshift, BigQuery)
Develop and maintain ETL/ELT workflows using Airflow
Write efficient, production-grade code in Python for data processing and integration
Partner with cross-functional teams (data, engineering, business stakeholders) to ensure data reliability and accessibility
Post-migration: support ongoing data operations, integrations, and enhancements
We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to HR@insightglobal.com.To learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy: https://insightglobal.com/workforce-privacy-policy/.
Required Skills & Experience
• Proficiency in SQL and Python with strong familiarity towards modern data engineering frameworks, infrastructure, and tooling. (Ideally 5+ Years)
• Proficiency with data ops best practices, monitoring, pipeline automation, and CI/CD.
• Knowledge of modern compute and ML frameworks/libraries (i.e., Spark, TensorFlow, PyTorch, scikit-learn).
• Hands-on experience with cloud data warehouses (Redshift and/or BigQuery)
• Experience building and maintaining data pipelines using Airflow/Airbyte
• Strong understanding of data modeling, ETL/ELT, and distributed data systems
• Comfort using AI tools in day-to-day workflows, with a willingness to continuously rethink and improve how work gets done.
• Curiosity and openness to experimenting with new tools and approaches; prior experience with AI tools is a plus.
Nice to Have Skills & Experience
• Bachelor’s degree (or equivalent) in Computer Science, Data Science, Statistics, Engineering or a related field.
• 5+ years of experience in data engineering, platform engineering, or ML engineering.
• Experience supporting a cloud migration (ideally AWS → GCP)
• Ability to build production APIs and services, inclusive of MCP servers that expose internal data/services to LLMs.
Benefit packages for this role will start on the 1st day of employment and include medical, dental, and vision insurance, as well as HSA, FSA, and DCFSA account options, and 401k retirement account access with employer matching. Employees in this role are also entitled to paid sick leave and/or other paid time off as provided by applicable law.