Amazon

Data Engineer, MIDAS, Digital Acceleration

Amazon Chennai, Tamil Nadu, India

Software Development · 10,001+ employees

21 h ago
data-engineer Mid (2-5 yrs) Full-time India
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About the role

Develop and maintain scalable data products, infrastructure, and pipelines using AWS services and internal tools. Collaborate with cross-functional teams including software developers, scientists, and product managers to drive data-driven decision-making.

What they look for

Data Engineering SQL Data Modeling ETL Python AWS Redshift Kinesis EMR Lambda Big Data Database Architecture Data Pipelines Spark Hive Automation

Requirements

Requires at least 1 year of data engineering experience with proficiency in SQL, data modeling, and ETL pipeline development. Candidates should have experience with scripting languages like Python and familiarity with big data technologies.

Full 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?

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.

Key job responsibilities 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.

2. Improve existing solutions/build solutions to improve scale, quality, IMR efficiency, data availability, consistency & compliance.

3. 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.

4. Drive operational excellence strongly within the team and build automation and mechanisms to reduce operations

About the team 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.

Basic Qualifications: - 1+ years of data engineering experience - Experience with SQL - Experience with data modeling, warehousing and building ETL pipelines - Experience with one or more query language (e.g., SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, Scala) - Experience with one or more scripting language (e.g., Python, KornShell)

Preferred Qualifications: - Experience with big data technologies such as: Hadoop, Hive, Spark, EMR - Experience with any ETL tool like, Informatica, ODI, SSIS, BODI, Datastage, etc.

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 https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

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