Director of Engineering Data Analytics Engines, Data Processing

Position: Director of Engineering for Open Data Analytics Engines, Data Processing & Experience
Description

AWS Open Data Analytics Engines is a suite of fully managed, high-performance analytics services built on popular open-source frameworks, enabling customers to process, analyze, and derive insights from massive datasets with speed, flexibility, and cost efficiency. Open Data Analytics Engines make it easy for organizations to run petabyte-scale analytics using familiar open-source tools without the operational burden of managing infrastructure.

AWS Open Data Analytics Engines encompasses services purpose-built for large-scale data processing, interactive querying, real-time streaming, and machine learning workloads. The platform leverages open-source engines such as Apache Spark, Presto/Trino, Apache Flink, and Apache Hive, delivering seamless integration with the broader AWS ecosystem. Compute and storage are decoupled, enabling elastic scaling, fine-grained cost optimization, and support for diverse data lake architectures.

As Director of Engineering for Open Data Analytics Engines, you will own the strategy and technical roadmap for innovations in engine efficiency, features, and performance. You'll lead a group of top talent in the design, development, and operation of next-generation open-source analytics services on AWS, driving advances in query planning and optimization, distributed execution, and cost-performance across the portfolio.

Key job responsibilities

Grow and lead a software development organization responsible for building key AWS analytics services based on open-source engines.

Drive the design, implementation, testing, and deployment of managed analytics services spanning batch processing, interactive queries, and real-time streaming.

Own the strategy and technical roadmap for innovations in engine efficiency, query planning and optimization, and performance - setting the direction for how AWS advances the state of the art in open-source analytics.

Draw from your deep and broad technical and management expertise to mentor senior engineers and managers, complete hands-on technical work, and provide leadership on complex technical issues, design tradeoffs, and feature and schedule prioritization.

Work with senior executives to develop business targets and resource requirements, influence technical and business strategy, hire talented engineers and managers, and conceive innovative new solutions for customers.

A day in the life

Leading the Open Data Analytics Engines team gives you the opportunity to:

Work on industry-defining products in the rapidly evolving open-source data analytics space

Solve challenging problems in distributed query execution, query planning and optimization, stream processing, resource scheduling, and performance optimization at cloud scale

Build products that deliver the power of open-source analytics with the reliability, security, and ease-of-use customers expect from AWS

Work for a company that is a recognized leader in cloud computing

Be involved in the fast-growing cloud analytics and data lake market

Develop and execute a strategic roadmap for the future of open-source analytics on AWS

Basic Qualifications

Bachelor's degree in Computer Science (or related field) or equivalent work experience

10+ years in the development of mission-critical system software, including work on distributed systems, large-scale data processing, or analytics platforms

5+ years managing engineering teams

Preferred Qualifications

5+ years partnering with sales, marketing, and customer success teams

Experience developing and deploying cloud-based analytics technology, particularly services built on open-source frameworks (Spark, Presto/Trino, Flink, Hive)

Deep knowledge of query planning and optimization in distributed query engines or relational databases, including experience with resource scheduling, data lake architectures, and performance optimization at petabyte scale

Experience operating services at global scale with stringent latency, throughput, and availability requirements

Advanced degree:
Masters or PhD in Computer Science or Engineering, or MBA or similar business qualification

Amazon is an equal opportunity employer and does not discriminate on the basis of protected…