Data Engineer II, Amazon

Amazon; London; On-site; GBP 60,000 - 80,000; Full time

Job summary

Amazon's Consumer Payments organization seeks a Data Engineer to enhance analytics and automate data pipelines. The role demands strong technical skills, including experience with AWS tools, SQL, and programming languages like Python. Ideal for self-starters capable of thriving in fast-paced environments, this position offers the opportunity to significantly impact global strategies and operations.

Qualifications

• 3+ years of data engineering experience required.
• Experience with data modeling and ETL pipelines essential.
• Proficiency in AWS technologies preferred.

Responsibilities

• Design and develop large-scale data structures for analytics.
• Work with product tech teams to build data integration pipelines.
• Collaborate on machine learning algorithms with Analysts and Product Managers.

Skills

Data modeling

ETL processes

SQL

Python

Spark

Tools

AWS Redshift

AWS Glue

AWS EMR

Kinesis

Job description

Amazon’s Consumer Payments organization is seeking a highly quantitative, experienced Data Engineer to drive growth through analytics, automation of data pipelines, and enhancement of self-serve experiences. You will succeed in this role if you are an organized self-starter who can learn new technologies quickly and excel in a fast-paced environment. In this position, you will be a key contributor and sparring partner, developing analytics and insights that global executive management teams and business leaders will use to define global strategies and deep dive businesses.
You will be part the team that is focused on acquiring new merchants from around the world to payments around the world. The position is based in India but will interact with global leaders and teams in Europe, Japan, US, and other regions. You should be highly analytical, resourceful, customer focused, team oriented, and have an ability to work independently under time constraints to meet deadlines. You will be comfortable thinking big and diving deep. A proven track record in taking on end-to-end ownership and successfully delivering results in a fast-paced, dynamic business environment is strongly preferred.
Responsibilities include but not limited to:
- Design, develop, implement, test, and operate large-scale, high-volume, high-performance data structures for analytics and Reporting.
- Implement data structures using best practices in data modeling, ETL/ELT processes, and SQL, AWS – Redshift, and OLAP technologies, Model data and metadata for ad hoc and pre-built reporting.
- Work with product tech teams and build robust and scalable data integration (ETL) pipelines using SQL, Python and Spark.
- Continually improve ongoing reporting and analysis processes, automating or simplifying self-service support for customers.
- Interface with business customers, gathering requirements and delivering complete reporting solutions.
- Collaborate with Analysts, Business Intelligence Engineers and Product Managers to implement algorithms that exploit rich data sets for statistical analysis, and machine learning.
- Participate in strategic & tactical planning discussions, including annual budget processes.
- Communicate effectively with product/business/tech-teams/other Data teams.

BASIC QUALIFICATIONS

- 3+ years of data engineering experience
- Experience with data modeling, warehousing and building ETL pipelines

PREFERRED QUALIFICATIONS

- Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
- Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)

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