Do you want to build the analytics to understand and accelerate large scale migrations to AWS? Migrating to AWS is one of the most impactful business decisions AWS customers make and we want your help to better understand our customers' migration journeys. For customers large and small, migrating to AWS can have an enormously positive impact on their costs, agility, and employee growth. Here in the Migration Services team, we're working closely with customers to invent new approaches to migrations, build scalable systems, and use machine learning to solve problems that haven't been solved yet.
We are looking for a self-driven Sr. Data Engineer with software development life cycle experience including CI/CD pipeline development, coding standards, code reviews, source control management, build processes, and automated testing. In this role, you will help a team of data engineers build fault-tolerant systems with scalability and performance in mind. You will get the exciting opportunity to interact with very large data sets in one of the most complex data warehouse environments. Our data pipeline employs serverless AWS components (SNS, SQS & Lambda) to combine metrics from multiple data sources including Amazon Redshift, Salesforce, and Amazon S3. You will have the opportunity to help business and engineering stakeholders determine which migration related metrics they should be tracking and extend our data engineering infrastructure.
Day-to-day you will:
• Partner with product management, sales, and business stakeholders to analyze data from disparate data sources and determine how we can accelerate their migrations.
• Design, implement, and maintain a data pipeline and analytical environment using third-party and in-house reporting tools, modeling metadata, and building reports and dashboards.
• Use creative problem-solving to automate the collection and analysis from available data sources in order to deliver actionable output.
• Iteratively improve analysis and identify new metrics to improve analytics.
Our team puts a high value on work-life balance. Most days, our entire team is co-located in the Boston office, but we're also flexible when people occasionally need to work from home. We generally keep core in-office hours from 10am to 4pm. About half of us come in earlier and the other half of us stay later.
Mentorship & Career Growth
Our team is dedicated to supporting new team members. Our team has a broad mix of experience levels and Amazon tenures, and we're building an environment that celebrates knowledge sharing and mentorship. Our senior engineers truly enjoy mentoring more junior engineers and engineers from non-traditional backgrounds through one-on-one mentoring and thorough, but kind, code reviews.
We care about your career growth. We try to assign projects and tasks based on what will help each team member develop into a better-rounded engineer and enable them to take on more complex tasks in the future.
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.
• 5+ years of work experience with ETL, Data Modeling, and Data Architecture.
• 5+ years of writing and optimizing SQL.
• 5+ years of programming experience in languages like Python, Ruby or Java.
• Demonstrable ability in data modeling, ETL development, and data warehousing, or similar skills
• Experience with reporting tools like QuickSight, Tableau, Excel or other BI packages
• Experience in working and delivering end-to-end projects independently.
• B.S. degree in mathematics, statistics, computer science or a similar quantitative field
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.
Pursuant to the San Francisco Fair Chance Ordinance, we will consider qualified applicants with arrest and conviction records.
Pursuant to the Los Angeles Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records