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Data Engineer II, FinAuto

Amazon

London

On-site

GBP 45,000 - 90,000

Full time

15 days ago

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Job summary

Join a forward-thinking company as a Data Engineer in the Finance Automation team, where you'll play a pivotal role in building a next-generation invoice matching system. This exciting position involves modernizing the architecture to be AI-ready, utilizing the latest AWS technologies, and ensuring high data quality visibility. You'll work with a talented team, tackling complex data challenges while contributing to a culture of innovation and collaboration. If you're passionate about data engineering and eager to make a significant impact, this opportunity is perfect for you.

Qualifications

  • Strong understanding of ETL and data modeling with large datasets.
  • Experience with AWS technologies and data warehousing best practices.

Responsibilities

  • Build and maintain ETL pipelines for large-scale data processing.
  • Collaborate with teams to democratize data access and drive innovations.

Skills

ETL Concepts
Data Modeling
SQL
Data Warehousing
Problem-solving
Scripting (UNIX Shell, Python)
Data Mining

Education

3+ years of data engineering experience
4+ years of SQL experience

Tools

AWS Redshift
AWS S3
AWS Glue
AWS EMR
Kinesis
FireHose

Job description

Finance Automation team at Amazon is looking for a Data Engineer to play a key role in building the next generation invoice matching system. Join us if you would like to be part of the exciting journey of further modernizing our architecture to be AI ready, leveraging Zero ETL, AWS Data Zone with end-to-end data lineage and 100% data quality visibility. The ideal candidate will be passionate about building next generation extremely large, scalable and fast distributed systems on AWS stack and will want to be part of a team that has accepted the goal to democratize access to data and enabling data-driven innovations for the entire Finance business in Amazon.


Looking for a candidate with a strong background in new age AWS stack (S3, EMR, Redshift) or traditional BI & DW with interest in data mining and the ability to sieve emerging patterns and trends from large amounts of data. Data Engineer should have strong experience with all standard data warehousing technical components (e.g. ETL, Reporting, and Data Modeling), infrastructure (e.g. hardware and software) and their integration. The ideal candidate will have extensive experience in dimensional modeling, excellent problem-solving ability dealing with huge volumes of data, and a short learning curve. Excellent written and verbal communication skills are required as the candidate will work very closely with diverse teams and senior leadership.


Join our exceptional team where you'll tackle challenging problems while working alongside industry-leading data engineering talent. We offer a premium work environment where you can make meaningful contributions, shape the future of data engineering, and enjoy the journey along the way.


Candidate should have :

  1. Strong understanding of ETL concepts and experience building them with large-scale, complex datasets using traditional or map reduce batch mechanism.
  2. Strong data modeling skills with solid knowledge of various industry standards such as dimensional modeling, star schemas etc.
  3. Extremely proficient in writing performant SQL working with large data volumes.
  4. Experience designing and operating very large Data Warehouses.
  5. Experience with scripting for automation (e.g., UNIX Shell scripting, Python).
  6. Good to have - experience working on AWS stack.
  7. Clear thinker with superb problem-solving skills to prioritize and stay focused on big needle movers.
  8. Curious, self-motivated & a self-starter with a ‘can do attitude’. Comfortable working in a fast-paced dynamic environment.
BASIC QUALIFICATIONS

- 3+ years of data engineering experience
- 4+ years of SQL 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)


Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit this link for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

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.

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