Sr. Data Engineer, AWS Security Assurance

Amazon Web Services
 Dallas, TX

Desciption

Job summary

Come join a creative and innovative Security Assurance team that drives exceptional security for customers and provides cutting edge technology solutions. The Amazon Web Services (AWS) business is rapidly expanding its global presence and we are looking for innovative people to develop and support business intelligence and operations reporting and management systems. In this role, you will support improvement and creation of metrics and dashboards. In addition, you will work with internal customers at all levels of the organization. We seek candidates that enjoy the challenges and rewards of working in a fast-growing organization and a very international environment.

As a Data Engineer, you will be working on most complex data warehouse environments. You will design, implement and support scalable data infrastructure solutions to integrate with multi heterogeneous data sources, aggregate and retrieve data in a fast and safe mode, curate data that can be used in reporting, analysis, machine learning models and ad-hoc data requests. You will be exposed to cutting edge AWS big data technologies. You should have excellent business and communication skills to be able to work with business owners and Tech leaders to gather infrastructure requirements, design data infrastructure, build up data pipelines and data-sets to meet business needs. You stay abreast of emerging technologies, investigating and implementing where appropriate.

Your major responsibilities will include

Key responsibilities include:

  • Design, build, and maintain data pipelines using modern Big Data technologies such as AWS Redshift, S3, Glue, Hammerstone, Athena, EMR, Spark, Hive, etc.
  • Utilize modern cloud database and storage concepts to for data storage and versioning (Data Lakes with AWS S3)
  • Establish scalable, efficient, automated processes for large scale data analysis
  • Build data pipelines to feed machine learning models for real-time and large-scale offline use cases.
  • Plan, design, implement, and manage a deployment of self-service data visualization platform (with front end as Tableau, QuickSight, and/or Apache Superset)
  • Support the development of performance dashboards that encompass key metrics to be reviewed with senior leadership and sales management
  • Work with business owners and partners to build data sets that answer their specific business questions
  • Support Business Operations Leads, Analysts and beyond in analyzing usage data to derive new insights and fuel customer success.

You demonstrate solid communication skills and the ability to partner with Research Scientists and business owners across technical and non-technical teams to develop and define key business questions, then build the solutions that answer those questions.

Inclusive Team Culture

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 we 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 14 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust.

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. Our senior members enjoy one-on-one mentoring. We care about your career growth as a passionate learner that is motivated to take on challenges.

Work/Life Balance

Our team also puts a high value on work-life balance. Striking a healthy balance between your personal and professional life is crucial to your happiness and success here, which is why we aren’t focused on how many hours you spend at work or online. Instead, we’re happy to offer a flexible schedule so you can have a more productive and well balanced life—both in and outside of work.

Basic Qualifications

  • Bachelor degree in Computer Science or related technical field.
  • 5+ years of experience as a Data Engineer or in a similar role.

Preffered Qualifications

  • 7+ years of experience as a Data Engineer, BI Engineer, Business/Financial Analyst or Systems Analyst in a company with large, complex data sources.
  • Strong SQL skills to query relevant datasets.
  • Experience with one of the functional scripting languages (Python, Scala etc.) to process semi-structured or unstructured data inputs.
  • Experience with data modeling, data warehousing, and building ETL pipelines.
  • Knowledge of data management fundamentals and data storage principles.
  • Knowledge of distributed systems as it pertains to data storage and computing.
  • Experience building/operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets.
  • Proven success in communicating with users, other technical teams, and senior management to collect requirements, describe data modeling decisions and data engineering strategy.
  • Knowledge of software engineering best practices across the development lifecycle, including agile methodologies, coding standards, code reviews, source management, build processes, testing, and operations.
  • Meets/exceeds Amazon’s leadership principles requirements for this role
  • Meets/exceeds Amazon’s functional/technical depth and complexity for this role

# Security Assurance

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.

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