Data Engineer

Key Skills

Java Programming, Python Programming, C++, C Programming, SQL, Cloud computing, Scala Programming, Machine learning techniques, Data science techniques, MATLAB Programming, PyTorch, TensorFlow, R Programming

Job Description

Job summary

Kumo’s mission is to empower innovators to get the most out of cloud services. We build technology that reimagines how people and automation combine to solve problems, remove risks, build with excellence, and drive business impact. We own critical cloud services used by all AWS customers to build, optimize, and operate at scale. Our broad portfolio of services includes AWS Health, Trusted Advisor, Well-Architected, re:Post, Recommendations & Insights, Self-Service Automation, Support Center, AWS Managed Services, all internal tools used by our global support teams including Command Center, Troubleshooting Console, Support Security, and the IT systems used by all Amazonians. AWS Kumo is a fast-growing, agile, and collaborative team of individuals with diverse backgrounds, located around the globe with larger teams in the U.S., Canada, South Africa, Costa Rica, Australia, and EU. We combine the culture of a startup, the innovation and creativity of an R&D lab, and the work-life balance of a progressive organization. If you are looking for your next great career adventure, please come join us.

We are looking for an excellent Data Engineer who is passionate about data and the insights that large amounts of data sets can provide. You should possess both a data engineering background and a business acumen that enables you to think strategically. You will experience a wide range of problem solving situations requiring extensive use of data collection and analysis. The successful candidate will work in lock-step with BI Engineers, Data scientists, ML scientists, Business analysts, Product Managers and other stakeholders across organization. You will:

• Develop and improve the current data architecture, data quality, monitoring and data availability.
• Collaborate with Data Scientists to implement advanced analytics algorithms that exploit our rich data sets for statistical analysis, prediction, clustering and machine learning
• Partner with BAs across teams to build and verify hypothesis to improve the AWS Support business.
• Help continually improve ongoing reporting and analysis processes, simplifying self-service support for customers
• Keep up to date with advances in big data technologies and run pilots to design the data architecture to scale with the increased data sets of customer experience on AWS.

Here at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazon’s culture of inclusion is reinforced within our 16 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust.

Work/Life Balance

Our team puts a high value on work-life balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.

Mentorship & Career Growth

Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded professional and enable them to take on more complex tasks in the future.

BASIC QUALIFICATIONS

• Bachelor’s degree in Computer Science or related technical field, or equivalent work experience.
• 5+ years of work experience with ETL, Data Modeling, and Data Architecture.
• 4+ years of work experience in writing and optimizing SQL.
• Knowledge of AWS services including S3, Redshift, EMR, Kinesis and RDS.
• Experience with Big Data Technologies (Hadoop, Hive, Hbase, Pig, Spark, etc.)
• Knowledge of distributed systems as it pertains to data storage and computing

PREFERRED QUALIFICATIONS

• Experience in ETL optimization, designing, coding, and tuning big data processes using Apache Spark or similar technologies.
• Experience with building data pipelines and applications to stream and process datasets at low latencies.
• Experience handling data - tracking data lineage, ensuring data quality, and improving discoverability of data.
• Knowledge of distributed systems and data architecture (lambda)- design and implement batch and stream data processing pipelines, knows how to optimize the distribution, partitioning, and MPP of high-level data structures.
• Experience with native AWS technologies for data and analytics such as Redshift Spectrum, Athena, S3, Lambda, Glue, EMR, Kinesis, SNS, CloudWatch, etc.