Data Engineer III

Zinnia is the leading technology platform for accelerating life and annuities growth, simplifying the experience of buying, selling, and administering insurance products. Our success is driven by a commitment to three core values: be bold, team up, deliver value. With over $180 billion in assets under administration, serving 100+ carrier clients, 2500 distributors, and partners, Zinnia enables more people to protect their financial futures. We are looking for an experienced Data Engineer to join our data engineering team. Your role will involve designing, building, and optimizing robust data pipelines and platforms that power our analytics, products, and decision-making. You will collaborate with data scientists, analysts, product managers, and other engineers to deliver scalable, efficient, and reliable data solutions. Your responsibilities will include designing, developing, and maintaining scalable big data pipelines using Spark (Scala or PySpark), Hive, and HDFS. You will also build and manage data workflows and orchestration using Airflow, write efficient production-grade code in languages like Python, Java, or Scala, and develop complex SQL queries for data transformation and reporting. Additionally, you will work on cloud platforms like AWS to deploy and manage data infrastructure and collaborate with data stakeholders to deliver high-quality data solutions. To be successful in this role, you should have strong experience with the Big Data stack, excellent programming skills, expertise in SQL, hands-on experience with Spark tuning and optimization, and familiarity with Airflow for data workflow orchestration. A degree in Computer Science, Engineering, or a related field, along with at least 5 years of experience as a Data Engineer, is required. You should also have a proven track record of delivering production-ready data pipelines in big data environments and possess strong analytical thinking, problem-solving, and communication skills. Preferred or nice-to-have skills include knowledge of the AWS ecosystem, experience with Trino or Presto for interactive querying, familiarity with Lakehouse formats, exposure to DBT for analytics engineering, experience with Kafka for streaming ingestion, and familiarity with monitoring tools like Prometheus and Grafana. Joining our team as a Data Engineer will provide you with the opportunity to work on cutting-edge technologies, collaborate with a diverse group of professionals, and contribute to impactful projects that shape the future of insurance technology.,