Senior Staff Developer, Sonatus

• Bachelor’s or Master’s degree in Computer Science, Information Systems, or a related field
• 10+ years of experience in data engineering, data platform engineering, or a similar role, with a strong focus on building and scaling data analytics platforms
• Proven experience with big data technologies (e.g., Apache Spark, Apache Flink, Apache Kafka) and cloud-based data platforms (e.g., AWS, Google Cloud, Azure)
• Expertise in designing and managing large-scale data pipelines and distributed data processing systems
• Strong knowledge of SQL and NoSQL databases, data lake solutions (e.g., Apache Iceberg, Big Query), and ETL processes
• Proficiency in programming languages such as Go, Java, or Scala for building data applications and automating workflows
• Experience with containerization and orchestration tools (e.g., Docker, Kubernetes) for deploying and managing data services
• Excellent problem-solving and analytical skills, with a keen attention to detail
• Strong communication skills, with the ability to articulate complex technical concepts to both technical and non-technical stakeholders
• Leadership abilities, with experience mentoring and guiding engineering teams

Desirable

• We are seeking a highly skilled and experienced Senior Staff Developer for Data Analytics to lead the design, development, and optimization of our data analytics platform
• This role requires a deep understanding of scalable data systems, cloud-native architectures, and advanced data processing frameworks
• You will play a key role in shaping the future of our data infrastructure, enabling our organization to derive valuable insights from vast amounts of data
• This position offers the opportunity to work on cutting-edge technologies and drive innovation in our data engineering practices
• Lead the design and implementation of a robust, scalable, and high-performance data analytics platform capable of handling large-scale data workloads
• Architect and optimize data pipelines for both real-time and batch processing, ensuring data is delivered accurately and efficiently across the organization
• Evaluate and select appropriate technologies and frameworks (e.g., Spark, Flink, Kafka, Presto) to build a modern data analytics platform that meets business needs
• Identify and address performance bottlenecks in the data platform, ensuring the system can scale to meet the growing data demands of the business
• Implement data partitioning, sharding, and indexing strategies to optimize query performance and reduce latency
• Ensure the platform is designed for high availability, reliability, and fault tolerance, minimizing downtime and ensuring business continuity
• Collaborate with software engineering, data engineering, and analytics teams to integrate data sources into the platform and ensure data quality and consistency
• Develop and enforce best practices for data governance, data security, and data management within the platform
• Implement data cataloging and metadata management tools to improve data discoverability and usability across the organization
• Lead cross-functional teams to deliver data-driven solutions that support business objectives and drive strategic initiatives
• Provide technical leadership and mentorship to junior engineers, fostering a culture of continuous learning and improvement
• Collaborate with product managers, data scientists, and other stakeholders to understand data requirements and translate them into scalable solutions
• Stay up to date with the latest advancements in data engineering, analytics, and cloud technologies, and apply them to enhance the platform
• Drive continuous improvement initiatives to streamline data processing workflows, reduce costs, and improve the overall efficiency of the data platform
• Contribute to the development of internal tools and frameworks that enhance the capabilities and performance of the data analytics platform