Software Development Engineer II - Data Engineering

Role Summary: We are seeking a talented and motivated Senior Software Development Engineer to join our high-performing Data Engineering team. In this role, you will contribute to building and maintaining the critical data infrastructure that handles hundreds of millions of requests per minute (RPM) for our ingestion services, processes billions of events daily from Kafka, and manages petabytes of data stored in data lake. You will work alongside senior engineers to implement scalable, reliable, and performant data solutions that directly impact our global user base. This is an excellent opportunity to grow your technical skills, contribute to meaningful projects, and be part of building the next generation of AI-powered experiences. Youll also be contributing to the data foundations for our AI initiatives, including working on data pipelines that support our MCP server and infrastructure for cutting-edge AI Agents, while learning from experienced engineers and growing your expertise in large-scale data systems.

Key Responsibilities

• Feature Implementation: Develop and implement features for data ingestion, processing, governance, observability and storage systems based on technical specifications and guidance from senior engineers
• Real-time Data Pipeline Contribution: Build components for highly scalable, accurate, and real-time event collection systems under the guidance of senior team members
• Data Pipeline Development: Implement data pipelines to support AI model training and autonomous AI Agents, ensuring data quality and reliability
• Code Quality: Write clean, maintainable, and well-tested code following established engineering standards and best practices
• System Maintenance: Contribute to improving existing systems and services using modern tooling and engineering practices
• Performance Optimization: Help identify and implement optimizations for ingestion, storage, and processing components

Skills

• Data Processing: Hands-on experience with data processing frameworks like Apache Spark, Apache Flink, or similar technologies for batch and streaming workloads
• AI/ML Pipeline Experience: Some exposure to building data pipelines for machine learning workflows, feature engineering, or model training (nice to have)
• Messaging Systems: Experience with messaging queues and stream processing platforms like Apache Kafka, Kinesis, or equivalent
• Cloud Platforms: Working knowledge of at least one major cloud platform (AWS, GCP, or Azure) and their data services, with preference for AWS (S3, EMR, Kinesis, etc.)
• Data Storage: Understanding of modern data warehousing and data lake concepts (Snowflake, BigQuery, Redshift, Delta Lake)
• ETL/Pipeline Tools: Experience building ETL/ELT pipelines using tools like Apache Airflow, Prefect, or similar orchestration systems
• Databases: Solid SQL skills and experience with both relational (PostgreSQL, MySQL) and NoSQL databases (Cassandra, DynamoDB)
• Monitoring: Experience with monitoring and observability tools (Datadog, Grafana, Prometheus etc.)
• IaC: Familiarity with Infrastructure as Code (Terraform, CloudFormation)

Qualifications

• Professional Experience: 2 - 4 years of software engineering experience with at least 2 years focused on data engineering or related fields
• Scale Exposure: Experience working with large datasets and high-throughput systems (millions of events, terabytes of data)
• Programming Skills: Proficiency in at least one major programming language such as Python, Java, Scala, or Go
• System Design Understanding: Basic understanding of distributed systems concepts and data processing patterns

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