Data Engineer II, FinAuto

Amazon; Hyderabad; On-site; INR 800,000 - 1,500,000; Full time

Job summary

Join a forward-thinking company as a Data Engineer and be part of an exciting journey to modernize data architecture. You'll leverage cutting-edge AWS technologies to build scalable and efficient data solutions that empower the Finance business. This role offers the opportunity to work with industry-leading talent, tackle complex challenges, and contribute to innovative data-driven projects. If you are passionate about data engineering and thrive in a dynamic environment, this is the perfect opportunity for you to make a meaningful impact and shape the future of data at a leading organization.

Qualifications

• 3+ years of data engineering experience and 4+ years of SQL experience.
• Experience with data modeling, warehousing, and building ETL pipelines.

Responsibilities

• Build next-generation invoice matching systems and modernize architecture.
• Work with large-scale datasets and ensure data quality visibility.

Skills

ETL concepts

Data modeling

SQL

Data Warehousing

Scripting (UNIX Shell, Python)

AWS technologies

Problem-solving

Data mining

Education

Bachelor's degree in Computer Science or related field

Tools

AWS Redshift

AWS S3

AWS Glue

AWS EMR

Kinesis

FireHose

Lambda

Job description

Finance Automation team at Amazon is looking for Data Engineer to play a key role in building 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 entire Finance business in Amazon.

Looking for a candidate with strong background in new age AWS stack (S3, EMR, Redshift) or traditional BI & DW with interest in data mining and ability to sieve emerging patterns and trends from large amount 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 modelling skills with solid knowledge of various industry standards such as dimensional modelling, 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 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)

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.