Data Engineer II, MIDAS, Digital Acceleration

Amazon.com, Inc.
United States
10 days ago
Apply on dejobs.org
Prepare application

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Experienced
Experience required
3 years minimum
Working hours
Regular working hours
Job source

Tech stack

Amazon Web Services Amazon S3 Build Automation Big Data Databases Information Engineering Extract Transform Load (ETL) Data Stores Graph Database Identity and Access Management SQL Databases IMR (Goal Tracking System)
+6 more
System Availability Electronic Medical Records AWS Glue Non-relational Database Data Pipelines Amazon Redshift

Job description

Are you excited about the digital media revolution and passionate about designing and delivering advanced analytics that directly influence the product decisions of Amazon’s digital businesses. Do you see yourself as a champion of innovating on behalf of the customer by turning data insights into action?, 1. Develop data products, infrastructure and data pipelines leveraging AWS services (such as Redshift, Kinesis, EMR, Lambda etc.) and internal BDT tools (Datanet, Cradle, QuickSight etc.

  1. Improve existing solutions/build solutions to improve scale, quality, IMR efficiency, data availability, consistency & compliance.
  2. Partner with Software Developers, Business Intelligence Engineers, MLEs, Scientists, and Product Managers to develop scalable and maintainable data pipelines on both structured and unstructured (text based) data.
  3. Drive operational excellence strongly within the team and build automation and mechanisms to reduce operations

Requirements

The Amazon Digital Acceleration (DA) org is looking for an analytical and technically skilled data engineer to join our team. In this role, you will play a critical part in developing foundational analytical datasets spanning orders, subscriptions, discovery, promotions, pricing and royalties. Our mission is to enable digital clients to easily innovate with data on behalf of customers and make product and customer decisions faster.

An ideal individual is someone who has deep data engineering skills around ETL, data modeling, database architecture and big data solutions. This individual should have strong business judgement, excellent written and verbal communication skills., * 3+ years of data engineering experience

  • 4+ years of SQL experience
  • Experience with data modeling, warehousing and building ETL pipelines, * 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)

About the company

The MIDAS team operates within Amazon’s Digital Analytics (DA) engineering organization, building analytics and data engineering solutions that support cross-digital teams. Our platform delivers a wide range of capabilities, including metadata discovery, data lineage, customer segmentation, compliance automation, AI-driven data access through generative AI and LLMs, and advanced data quality monitoring. Today, more than 100 Amazon business and technology teams rely on MIDAS, with over 20,000 monthly active users leveraging our mission-critical tools to drive data-driven decisions at Amazon scale.

Apply for this position

This job is hosted externally. Click below to view the full posting and apply.

Apply on dejobs.org
Prepare application

Good distractions

Talks and stories from around this role — technically off-topic, practically not.

3:28 min

Defining big data and machine learning fundamentals

Ayon Roy · LIVE

55 sec

Validating data processing architectures via containerized events

Modood Alvi · World Congress 2025

3:43 min

The enduring legacy of the amazon S3 storage API

Chris Heilmann +3 · LIVE

3:03 min

Career evolution in data engineering and AI platforms

Maria Apazoglou · Coffee With Developers

2:10 min

Why organizations combine big data and machine learning

Ayon Roy · LIVE

3:09 min

Balancing data science skillings alongside systems engineering rigor

Nico Schmidt · LIVE

Videos

See all

Related articles

See all