Sr Data Engineer

As the leading technology platform for accelerating life and annuities growth, Zinnia simplifies the experience of buying, selling, and administering insurance products. With a commitment to core values such as being bold, teaming up, and delivering value, Zinnia has over $180 billion in assets under administration, serves 100+ carrier clients, 2500 distributors and partners, and over 2 million policyholders. Joining the data team at Zinnia means contributing to the company's goal of uncovering opportunities and making data-driven decisions. Working closely with stakeholders from various departments, the data team focuses on developing deeper predictors of behavior, insights that drive business strategy, and solutions to optimize internal and external experiences. Your responsibilities will include overseeing technological choices and implementing data pipelines and warehousing philosophy, leading cross-organizational projects automating data value chain processes, promoting technical best practices, designing simple and maintainable data architecture, mentoring team members, designing data pipelines, enforcing data governance and security, and partnering with product and engineering teams to maximize downstream data. To excel in this role, you should have extensive experience with data engineering techniques, Python, and SQL. Familiarity with tools like Airflow and dbt is required, along with expertise in data engineering tooling such as jira, git, buildkite, terraform, and containers. Understanding ETL patterns, modern data warehousing concepts, data quality practices, and a passion for all things data are essential. You should enjoy both high-level architecture and low-level coding, be proactive in learning and teaching, and be willing to take risks to find innovative solutions. Technologies you will use include Python, Airbyte, Google Cloud Platform, Terraform, Kubernetes, Cloud SQL, Cloud Functions, BigQuery, DataStore, Airflow, dbt, Tableau, and PowerBI. Join Zinnia's data team to be part of a culture of learning, innovation, and empowerment, where you can challenge yourself to constantly improve and contribute to delivering value from data to both internal and external clients.,