📊 Senior Data Engineer – Scalable Pipelines for AI Agent Infrastructure

We’re looking for a Senior Data Engineer to design, build, and maintain the data foundation behind our next-generation AI agent platform. You’ll work closely with AI/ML teams to power training, inference, and continuous learning through highly scalable data pipelines and cloud-native architectures.

If you’re passionate about data infrastructure, performance optimization, and driving data quality at scale, we want to hear from you.

🗓 Start date: ASAP
📆 Contract type: Contractor - Indefinite
🌐 Work hours: Monday to Friday, 7.30 am to 4.30 pm PST - 100% Remote

🛠️ What You’ll Be Doing

• Build scalable ETL/ELT pipelines to support AI agent training and inference.
• Integrate data from diverse sources (APIs, databases, real-time streams).
• Design high-performance data models using PostgreSQL and Snowflake.
• Optimize SQL queries for large datasets and data warehouse workloads.
• Implement data validation, cleansing, and monitoring workflows.
• Automate data engineering tasks and contribute to CI/CD pipelines.
• Collaborate with AI/ML engineers and product teams to align data with business needs.
• Document processes, pipelines, and infrastructure decisions clearly.

✅ What You Need to Succeed

Must-haves

• 5+ years of experience in Data Engineering or Data Infrastructure roles.
• Strong command of:
  • ETL frameworks: Airflow, DBT, Spark
  • Databases: PostgreSQL, Snowflake
  • Cloud & DevOps: AWS (S3, EC2), Linux, Docker
  • CI/CD: GitHub, Jenkins or similar
  • Programming: Python (data-focused scripting)
• Deep knowledge of SQL performance tuning, data warehousing, and data quality practices.
• Experience with data security and managing large-scale database environments.
• Comfortable working in cross-functional teams and agile environments.

Nice-to-haves

• Experience with AWS RDS, MWAA, Lambda.
• Familiarity with vector databases and retrieval-augmented generation (RAG) pipelines.
• Exposure to prompt engineering, LLM workflows, or AI/ML data operations.
• Data Engineering certification (GCP, AWS, or equivalent).

🧭 Our Recruitment Process

Here’s what to expect from our candidate-friendly interview process:

1. Initial Interview – 60 minutes with our Talent Acquisition Specialist

2. Culture Fit – 30 minutes with our Team Engagement Manager

3. Technical Assessment - Python Coding + Multiple Choice questions

4. Final Stage – 60 minutes with the Hiring Manager (Technical Interview)

🌟 Why Join Launchpad?

We believe that great work starts with great people. At Launchpad, we offer:

• 💻 Fully remote work with hardware provided

• 🌎 Global team experience with clients in [regions]

• 💸 Competitive USD compensation

• 📚 Training and learning stipends

• 🌴 Paid Time Off (vacation, personal, study)

• 🧘‍♂️ A culture that values autonomy, purpose, and human connection

✨ Join us and help shape the future of intelligent systems—one data pipeline at a time.