Job Details

Big Data Engineer

Advertiser
Amazon Web Services
Location
Dallas, Texas, United States
Rate
-
Description

Job summary

Amazon Web Services (AWS) is the leading platform for designing and developing applications for the cloud and is growing rapidly with hundreds of thousands of companies in over 190 countries on the platform. The Worldwide Revenue Operations (WWRO) team will be the authoritative source of customer metadata and the solutions team for applications that action AWS' strategies to better serve our customers. We invest resources in information and solutions enabling AWS sales and business teams that yield increased customer adoption and an optimal customer experience.

Are you an experienced Big Data Engineer passionate about building scalable, enterprise-level systems? We are looking for a Big Data Engineer to play a key role in building next generation tools and solutions. In addition to technical expertise, you will invest time to understand the needs of the business, the data behind it, and how to transform information into technical solutions that allow the business to take action.

You should have deep expertise in the design, creation, management, and business use of large datasets, across a variety of data platforms. You should have excellent business and interpersonal skills to be able to work with business owners to understand data requirements, and to build ETL to ingest the data into the data lake. You should be an authority at crafting, implementing, and operating stable, scalable, low cost solutions to flow data from production systems into the data lake. Above all you should be passionate about working with huge data sets and someone who loves to bring datasets together to answer business questions and drive growth.

This position may be based in Seattle (WA), Dallas (TX), Boston (MA), New Jersey/New York, Atlanta (GA) or Arlington (VA). Relocation offered for US residents only.

About Us

Inclusive Team Culture

Here at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have twelve 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 14 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

This position requires a Bachelor's Degree in Computer Science or a related technical field, and 7+ years of relevant work experience.

5+ years of work experience with ETL, Data Modeling, and Data Architecture.

Expert-level skills in writing and optimizing SQL.

Experience with Big Data technologies such as Hadoop, Hive/Spark.

Proficiency in one of the scripting languages - python, ruby, linux or similar.

Experience operating very large data warehouses or data lakes.

PREFERRED QUALIFICATIONS

Authoritative 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.

Demonstrate efficiency in handling data - tracking data lineage, ensuring data quality, and improving discoverability of data.

Sound 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.

Knowledge of Engineering and Operational Excellence using standard methodologies.

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

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

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