Amazon Financial Technology Team is looking for a results-oriented data engineer, who can help us build the next generation of distributed, scalable financial systems. Our ideal candidate thrives in a fast-paced environment, enjoys the challenge of highly complex business contexts that are typically being defined in real-time. We need someone to design and develop data solutions that facilitate global financial transactions worth billions (USD) annually.
As a data engineer, you will get the exciting opportunity to work on very large data sets in one of the world's largest and most complex data warehouse environments. You will work closely with the business teams in analysis on various cost savings initiatives, many non-standard and unique business problems and use creative-problem solving to deliver actionable output.
You will be responsible for designing and implementing an analytical environment using third-party and in-house reporting tools, modeling metadata, building reports and dashboards. You will have an opportunity to work with leading edge technologies like Redshift, Hadoop/Hive/Pig. You will be writing scalable queries and tuning performance on queries running over billion of rows of data.
You should be analytical, have a high level of customer focus and a passion for process improvement. You should be motivated self-starter that can work in a fast paced, ambiguous environment. You should have excellent business and communication skills to be able to work with business owners to develop and define key business questions.BASIC QUALIFICATIONS
• 5+ years of experience as a Data Engineer or in a similar role
• Experience with data modeling, data warehousing, and building ETL pipelines
• Experience in SQL
• Knowledge of batch and streaming data architectures
• Experience with AWS technologies including Redshift, RDS, S3, EMR, EML or similar solutions built around Hive/Spark etc.
• Experience communicating with senior management as well as with colleagues from engineering, analytics, and business backgrounds.
• Exceptional written communication skills
• Experience using big data technologies (Hadoop, Hive, HBase, Spark etc.)
• Demonstrated strength in data modeling, ETL development, and data warehousing
• Knowledge of data management fundamentals and data storage principles
• Knowledge of distributed systems as it pertains to data storage and computing
• Proficiency in Python or other similar languages.PREFERRED QUALIFICATIONS
• Masters in computer science, mathematics, statistics, economics, or other quantitative fields.
• Knowledge of software engineering best practices across the development lifecycle, including agile methodologies, coding standards, code reviews, source management, build processes, testing, and operations
• Excellent knowledge of Advanced SQL working with large data sets.
• Knowledge of Advanced Statistics and implementing ML models.
• Demonstrated ability to mentor junior team members in all aspects of their engineering skill-sets
• Proven success in communicating with users, other technical teams, and senior management to collect requirements, describe data modeling decisions and data engineering strateg
• Experience providing technical leadership and mentoring other engineers for best practices on data engineering
• Strong business acumen, proven ability to influence others, strong attention to detail, excellent organization skills, and ability to manage multiple projects