Senior BigData Operations Engineer

February 7

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Diabetes Youth Families

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Diabetes Youth Families is a company that provides wearable insulin delivery solutions for diabetes management. Their primary products, such as the Omnipod 5 and Omnipod DASH systems, offer tubeless and automated insulin delivery for people with Type 1 and Type 2 diabetes, allowing users to manage their condition without the need for multiple daily injections. The systems integrate with continuous glucose monitoring (CGM) devices and can be controlled via compatible smartphones, enhancing the freedom and lifestyle of individuals living with diabetes. With a focus on reducing the burden of diabetes management, they offer financial assistance, support resources, and trial programs to help users adapt to their innovative solutions. The company emphasizes making life simpler while managing diabetes through technology-driven insulin management systems.

11 - 50 employees

Founded 1938

⚕️ Healthcare Insurance

🔧 Hardware

📋 Description

• Monitor and manage data pipelines to ensure the timely and accurate flow of data. • Resolve quality checks alerts to ensure the accuracy, completeness, and consistency of data. • Monitor and optimize data pipeline performance to meet and exceed established service level agreements (SLAs). • Collaborate with data engineering, data stewards, data owner teams to implement improvements in data quality processes and data pipeline performance. • Collaborate with IT Ops and SRE for building a robust monitoring pipeline. • Implement proactive measures to identify and resolve data issues automatically. • Maintain comprehensive documentation of data operations processes, monitoring procedures, and issue resolution protocols. • Ensure documentation and operating procedures are up to date to facilitate knowledge transfer and training. • Well understanding of CI/CD technologies and incorporate Terraform and automation of Infrastructure and pipelines. • Well understanding of Databricks and Databricks Access Bundles and incorporate automation and well architected data operations.

🎯 Requirements

• 5+ years’ experience in hands-on data operations including data pipeline monitoring, support and engineering. • Experience in data Quality Assurance, Control and Lineage for large datasets in relational/non-relational databases is strongly preferred. • Experience managing robust ETL/ELT pipelines for big real-world datasets that could include messy data, unpredictable schema changes and/or incorrect data types is strongly preferred. • Proficiency in Databricks, AWS and/or Azure, or similar cloud platforms. • Experience monitoring, and supporting data pipelines that are fast, scalable, reliable, and accurate. • Strong analytical and problem-solving skills, with a keen attention to detail. • Effective communication and collaboration abilities. • Experience with big data technologies such as Apache Spark, Hadoop, and Kafka. • Expertise in data modeling, ETL processes, and data warehousing. • Experience with both batch data processing and streaming data. • Experience in implementing and maintaining Business Intelligence tools linked to an external data warehouse or relational/non-relational databases is required.