Senior Software Engineer, Affinity

• 5+ years of experience as a Software Engineer or Data Engineer with at least 2-3 years in a Senior Engineering role, leading complex, and sometimes ambiguous, engineering projects across team boundaries
• Proficiency in event streaming and batch processing pipelines for data-intensive applications is essential
• Proven hands-on experience with scalable and robust distributed data systems using Kafka, AWS SQS or similar technologies
• Comfortable working with large datasets and high-scale data ingestion, transformation, and distributed processing tools such as Apache Spark
• Strong proficiency in SQL
• Experience with cloud platforms such as AWS, Databricks, GCP, Azure or related technologies
• Familiar with CI/CD processes and test frameworks
• Comfortable partnering with product and machine learning teams on large, strategic data projects
• Don’t meet every single requirement? Studies have shown that women and people of color are less likely to apply for jobs unless they meet every qualification. At Affinity, we are dedicated to building a diverse, inclusive, and authentic workplace, so if you’re excited about this role but your past experience doesn’t perfectly align with the qualifications above, we encourage you to apply anyways. You may be just the right candidate for this or other roles

Desirable

• This role is part of the AI Insights team, which owns the services that power Affinity's industry-leading relationship intelligence platform. Our team extracts and retrieves information from billions of structured and unstructured data points to deliver insights to our customers
• As a Senior Software Engineer, Data, you will collaborate with machine learning engineers, software engineers, and product managers to shape the future of private capital's leading CRM platform
• This involves designing and building scalable, efficient event streaming processing pipelines and batch processing pipelines to transform and load data into distributed data storage. You will play a key role in enhancing our frameworks to monitor data quality, safeguard data security, and implement best practices
• Design scalable and reliable data pipelines to consume, integrate and analyze large volumes of complex data from different sources, supporting the evolving needs of our business
• Help define our data roadmap. You'll collaborate with our team of machine learning engineers, software engineers, product, and business leaders to shape product development
• Build and maintain frameworks for measuring and monitoring data quality and integrity
• Establish and optimize CI/CD processes, test frameworks, and infrastructure-as-code tooling
• Build and implement robust data-intensive applications over distributed systems
• Articulate the trade-offs of different approaches to building data pipelines and storage solutions, providing clear recommendations aligned with product and business requirements
• Tech Stack: Our Data stack includes tools to build data pipelines between AWS RDS and DBX via scheduled batch jobs and streaming syncing. Spark SQL and MLlib for large-scale data processing in DBX. We also build data pipelines between RDS and other search-optimized engines, such as openSearch. In-house data quality tools and governance tools to ensure data quality, security and compliance