Data Engineer II, Fire TV

Amazon; India; On-site; INR 1,800,000 - 3,200,000; Full time

Job summary

Amazon in India is seeking a Data Engineer to design, build, and operate large-scale data pipelines and datasets. You will partner with Data Science, BI, Product, Finance, and Engineering to deliver scalable data solutions across engagement analytics, advertising, and appstore performance.

You will own data platforms, ensure data quality, and work on Redshift, data lakes, and AWS services while mentoring teammates and driving reliability and compliance across teams.

Qualifications

• 3+ years of data engineering experience.
• Experience with data modeling, warehousing and ETL pipelines.
• Experience with one or more query languages (SQL, PL/SQL, HiveQL, SparkSQL).
• Experience with data lake/data warehouse solutions.
• Experience with Python or Scala.
• Experience with AWS technologies (Redshift, S3, Glue, EMR, Kinesis, Lambda).
• Experience with non-relational stores and governance/compliance concepts.
• Experience with big data technologies (Hadoop, Spark, Hive).
• Experience leveraging AI to build data-backed solutions.

Responsibilities

• Own design, development, testing, deployment, and operation of data pipelines and datasets.
• Build scalable ETL/ELT workflows using SQL, Python, and AWS services.
• Operate data infra including Redshift clusters, data lakes, and orchestration workflows.
• Improve reliability, automate recurring tasks, and draft runbooks.
• Collaborate with cross-functional teams to translate requirements into scalable data solutions.
• Develop data products for analytics, forecasting, and AI-enabled insights.
• Support compliance, privacy, retention, and governance initiatives.
• Participate in on-call and product support for critical pipelines.

Skills

Data modeling

ETL pipelines

SQL

Python

AWS

Big data

Data quality

Data governance

Tools

Redshift

S3

AWS Glue

EMR

Kinesis

Lambda

Hadoop/Spark

Hive

Job description

Fire TV, Advertising and Appstore is reshaping the way millions of people discover, engage with, and enjoy entertainment every day. The FAA Decision Science organization is looking for a Data Engineer to help build scalable, reliable, and compliant data systems that support millions of customers worldwide.

This role contributes to the foundational data infrastructure used by Data Science, Business Intelligence, Product, Finance, Advertising, Engineering, and leadership teams to make high-quality business decisions. You will design, build, and operate data pipelines, data models, data quality mechanisms, and cloud-based infrastructure supporting Fire TV engagement, lifecycle analytics, Ads monetization, Appstore performance, executive reporting, forecasting, experimentation, and AI-enabled analytics.

This role is appropriate for an engineer who can independently own defined data systems or workstreams while partnering with senior engineers and cross-functional stakeholders on broader technical direction. You will be expected to work through moderate ambiguity, clarify requirements, make sound implementation trade-offs, improve operational reliability, and deliver scalable solutions that reduce manual effort over time. Successful engineers in this role improve reliability, automate recurring work, simplify data systems, document operational processes, and build trusted data products that help the business move faster.

Key job responsibilities

• Own the design, development, testing, deployment, and operation of data pipelines and datasets within an assigned domain
• Build and maintain scalable ETL/ELT workflows using SQL, Python, AWS services, and big data technologies
• Operate and improve data infrastructure, including Redshift clusters, data lake tables, orchestration workflows, monitoring, alerting, and data quality controls
• Improve operational reliability by identifying recurring failures, reducing manual intervention, automating recovery steps, and creating clear runbooks
• Partner with Data Science, Business Intelligence, Product, Finance, Engineering, Privacy, and Legal stakeholders to translate business and compliance requirements into scalable data solutions
• Build and operate conversational, self-service, and agentic analytics data products
• Support compliance, privacy, retention, and governance initiatives, including GDPR, DMA, telemetry migration, data access controls, and retention workflows
• Contribute to data foundations that support forecasting, experimentation, ML/AI use cases, self-service analytics, and certified business metrics
• Implement data validation, lineage, documentation, and operational mechanisms that improve trust and reduce single points of failure
• Drive scoped modernization efforts such as pipeline simplification, migration support, Redshift/data lake improvements, automation, and self-service data enablement
• Clarify ambiguous requirements, identify data quality or source-of-truth gaps, and elevate broader trade-offs to senior engineers or managers when appropriate
• Mentor junior engineers on scoped technical tasks, coding standards, operational practices, and data quality expectations
• Participate in on-call and product support for business-critical pipelines and datasets
• Own the design and operation of the data foundations that power GenAI, RAG, and agentic analytics within an assigned domain
• Build guardrails, validation, and evaluation mechanisms, both automated and human-in-the-loop, that keep AI-generated outputs such as SQL and metrics accurate and reliable
• Apply AI coding assistants and agentic development tools to your daily work and share effective patterns with the team to raise overall engineering velocity.

Experience

• - 3+ years of data engineering experience
• - 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 database, data warehouse or data lake solutions
• - Experience with one or more scripting language (e.g., Python, KornShell, Scala)
• - 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)
• - Experience implementing scalable compliance solutions (technology, procedures, processes, etc.) in a regulated environment
• - Experience with big data technologies such as AWS, Hadoop, Spark, Pig, Hive etc.
• - Experience leveraging AI to build customer facing solutions and/or improving internal productivity
• - Experience handling AI/ML infrastructure

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