Senior AWS Data Platform Engineer

Zinnia; United States; Remote; USD 140,000 - 190,000; Full time

Job summary

Zinnia, the leading technology platform for accelerating life and annuities growth, seeks a Data Engineer to build pipelines, storage, and platform foundations powering analytics and products.

You will design well‑modeled data, reliable orchestration, and scalable infrastructure on AWS, using SQL, Python, Snowflake, Airflow, dbt, Terraform, and containerized services. Collaborate with engineers, analysts, and data scientists to deliver trusted data at scale.

Qualifications

• 4+ years of experience in Data Platform Engineering.
• Hands-on with AWS core services (S3, IAM, compute).
• Proficient in SQL and Python for data transformation and pipelines.
• Experience with Snowflake or similar data warehouse.
• Familiar with Airflow for orchestration and scheduling.
• Knowledge of dbt for transformations and testing.
• Solid data modeling fundamentals and teamwork in agile environments.

Responsibilities

• Build and maintain scalable data platforms and pipelines powering analytics.
• Work within AWS infrastructure, provisioning data components with Terraform.
• Implement telemetry, observability, and reliability improvements.
• Package and manage pipeline components as containerized services (Docker/Kubernetes).
• Develop ELT/ETL workflows using Airflow, dbt, and Airbyte.
• Contribute to data governance and cost optimization in AWS and Snowflake.
• Troubleshoot pipeline and infra issues with senior engineers; write docs.

Skills

SQL

Python

Data modeling

Communication

Tools

Snowflake

Airflow

dbt

Terraform

Kubernetes

Airbyte

GitHub Actions

Job description

Zinnia, the leading technology platform for accelerating life and annuities growth, seeks a Data Engineer to build pipelines, storage, and platform foundations powering analytics and products.

You will design well‑modeled data, reliable orchestration, and scalable infrastructure on AWS, using SQL, Python, Snowflake, Airflow, dbt, Terraform, and containerized services. Collaborate with engineers, analysts, and data scientists to deliver trusted data at scale.