Key skills
Distributed systems conceptsDebugging across application and infrastructure layersStorage API semantics consistencyStorage API semantics eventual visibilityStorage API semantics multi-part uploadsNetwork I/O and data localityResource scheduling and JVM tuningHigh throughput scalable systemsApache SparkApache FlinkApache KafkaJavaObject-oriented designData structuresAlgorithmsOptimizationSnowflakeClickhouseTrinoApache IcebergParquetApache ArrowApache HudiData modelingData accessChange Data Capture (CDC)Infrastructure as codeTerraformJava Spring BootGradleDynamoDBApache PulsarPostgreSQLPlanetscaleRedisAWSReactTypeScriptGraphQLStorybookRadix UIViteesbuildAIMLAnalyticsSparkKafka
About this role
Attentive is the AI marketing platform for 1:1 personalization redefining the way brands and people connect. The Senior Software Engineer will focus on architecting high-throughput solutions and enhancing self-service platforms to support data-driven products and strategic outcomes for customers.
Responsibilities:
- Architect high-throughput solutions that power our most critical operations, ensuring scalability and efficiency
- Expand and enhance our self-service platform, collaborating with cross-functional teams to fuel our AI, ML, and analytics goals
- Tackle complex distributed data challenges, streamline system integrations, and uphold high standards of quality and governance
- Champion cutting-edge technologies, keeping our platform at the forefront of industry advancements and enabling strategic outcomes
- Unify data from diverse systems, paving the way for experimentation and innovation while empowering teams with intuitive tools and frameworks
Requirements:
- Track record of debugging issues across layers—from application logic to infrastructure bottlenecks—and understand the tradeoffs in system design, not just the settings in a managed UI
- You don't just know how to run jobs in tools, you understand how they operate under the hood and how connected storage impacts performance like, How simple storage API semantics (e.g. consistency, eventual visibility, multi-part uploads) affect job execution, The impact of network I/O and data locality on performance and cost, The way resource scheduling and JVM tuning influence distributed job behavior
- Proven experience as a Software Engineer with a focus on high throughput scalable systems
- In-depth knowledge of high throughput processing technologies such as Spark, Flink, and/or Kafka
- Proficiency in Java and strong understanding of object-oriented design, data structures, algorithms, and optimization
- You have development experience working with data warehouse tools like Snowflake, Clickhouse, Trino, etc
- You've experience with open source data storage formats such as Apache Iceberg, Parquet, Arrow, or Hudi
- You are knowledgeable about data modeling, data access, and data replication techniques, such as CDC
- You have a proven track record of architecting applications at scale and maintaining infrastructure as code via Terraform
- You are excited by new technologies but are conscious of choosing them for the right reasons