10+ years of experience in designing, developing, and operating large-scale backend or data-intensive systems.
Proven experience owning and managing mission-critical data platforms in production environments.
Demonstrated success operating at a Senior or Staff Engineer level, delivering high-impact technical solutions.
Strong understanding of AI-native software development practices, including AI-assisted code generation, intelligent testing, and human-in-the-loop review processes.
Experience driving modern engineering practices by integrating AI into development workflows to improve engineering productivity, software quality, and delivery speed.
Technical Skills:
Strong proficiency in Python and SQL.
Extensive hands-on experience with distributed data processing and streaming technologies, including:
1.
Apache
Spark
2.
Apache
Kafka
3.
Apache
Flink
4.
Apache
Hive
Trino/Presto
Deep understanding of distributed systems, including scalability, data consistency, fault tolerance, and high availability.
Experience designing and operating cloud-native data platforms on Amazon Web Services (AWS).
Strong knowledge of data modeling, ETL/ELT architecture, query optimization, and performance tuning.
Familiarity with data warehousing, data lakes, and modern analytics architectures.
Engineering Mindset:
Comfortable working in fast-paced, ambiguous environments while making strategic technical decisions.
Strong expertise in system architecture, data modeling, and designing scalable, maintainable solutions.
Ability to balance short-term delivery with long-term architectural goals.
Proven ability to influence engineering teams, drive technical direction, and mentor peers without formal authority.
Passion for engineering excellence, operational reliability, and continuous improvement.
AI-Enabled Development:
Hands-on experience using AI-powered engineering tools such as GitHub Copilot, ChatGPT, Cursor, or similar platforms to accelerate software design, development, debugging, and documentation.
Strong ability to evaluate, validate, and optimize AI-generated code for correctness, security, scalability, and performance.
Experience incorporating AI into software development workflows to enhance developer productivity and software quality.
Understanding of prompt engineering and best practices for responsible AI-assisted software development.
Preferred Qualifications:
Experience building large-scale data platforms supporting analytics, machine learning, or AI workloads.
Knowledge of modern data lakehouse technologies such as Delta Lake, Apache Iceberg, or Apache Hudi.
Experience with Infrastructure as Code (Terraform, CloudFormation), containerization (Docker), and orchestration platforms (Kubernetes).
Familiarity with CI/CD pipelines, observability, monitoring, logging, and incident management.
Excellent communication, collaboration, and stakeholder management skills across cross-functional teams.
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