Alexa Communications is building the next generation of competitive analytics and modeling services. We are looking for an outstanding Data Engineer to design and implement robust, scalable, cloud-based data crunching systems at massive scale.
If you enjoy working with world-class data scientists and engineers, wrangling large data sets, developing efficient, rock-solid solutions, and delivering high quality analytics services to leaders, engineers, machine learning scientists, and data scientists this may be the right opportunity for you. We are looking for the best and brightest to join our Real-Time Analytics team, where you will create elegant and scalable solutions to complex technical problems and contribute to shaping the technical vision of our company.
· Design and develop robust, distributed processing solutions in our cloud (AWS) environment
· Evaluate and implement massive, scalable data storage solutions
· Optimize automated processes for performance and fault tolerance
· Optimize support for ad-hoc analysis across various data sources
· Optimize for runtime machine learning inference
· Provide operational support for critical systems
· Collaborate with peer technologists and contribute meaningfully in areas such as data science and security
· Bachelors Degree or higher in Computer Science, Statistics, or Mathematics
· 5+ years of experience as a Data Engineer or in a similar role
· 3+ years of hands-on experience in writing complex, highly-optimized SQL queries across large data sets.
· 2+ years of experience in scripting languages like Python etc
· Demonstrated strength in data modeling, ETL development, and Data warehousing
· Knowledge of advanced algorithms, data structures, and software engineering best practices
· Experience with AWS services including S3, Redshift, EMR and RDS
· Experience with Big Data Technologies (Hadoop, Hive, Spark, etc.)
· Experience in working and delivering end-to-end projects independently.
· Knowledge of distributed systems as it pertains to data storage and computing
· Proven success in communicating with users, other technical teams, and senior management to collect requirements, describe data modeling decisions and data engineering strategy
· Experience providing technical leadership and mentoring other engineers for best practices on data engineering
· Knowledge of software engineering best practices across the development lifecycle, including agile methodologies, coding standards, code reviews, source management, build processes, testing, and operations
· Masters in computer science, mathematics, statistics, economics, or other quantitative field