📋 Job Details at a Glance 📍 Location Bengaluru, KA, India 🏢 Company Amazon 👥 Experience 4+ years 🎓 Qualification 4+ years. Hands-on with SQL. Relevant technical qualification and demonstrated shipping experience 📅 Eligible Batch 2023, 2024, 2025, 2026 📄 Job Type Full Time 💰 Salary Not Disclosed 🏢 Industry Technology 🛠 Key Skills SQL data modeling warehousing ETL pipelines Data Engineer II, Alexa AI - ML Engineering at Amazon — Full Details & How to Apply Amazon is seeking a Data Engineer II, Alexa AI - ML Engineering for its team in Bengaluru, KA, India . This role requires 4+ years of hands-on SQL experience and involves building ETL pipelines that support Alexa AI’s machine learning operations. Candidates must have demonstrated shipping experience and a relevant technical qualification to qualify. This Data Engineer II, Alexa AI - ML Engineering role is essential for developing and maintaining ETL pipelines that ensure data integrity and support machine learning models in Alexa AI. The position directly enables efficient data processing by structuring data through data modeling and warehousing , which feeds into AI training pipelines. The core responsibilities focus on SQL , data modeling , and ETL pipeline development—skills that are foundational to reliable data flow in AI systems. The job posting identifies Amazon as a technology company with a dedicated Alexa AI - ML Engineering team. This role is part of Amazon ’s recruitment efforts in the field of machine learning engineering, with a focus on data infrastructure in Bengaluru, KA, India. The team operates in a technical environment that values hands-on experience and proven technical delivery. 2023, 2024, 2025, 2026 graduates are eligible. Candidates must have 4+ years. Hands-on with SQL. Relevant technical qualification and demonstrated shipping experience . The role demands 4+ years experience and requires a strong foundation in technical data engineering. Salary is not disclosed . Applicants will gain hands-on experience with SQL , data modeling , and ETL pipelines . These skills are directly applicable to data-driven AI systems and provide a pathway to advanced roles in machine learning engineering or data science. The role offers a progression into specialized AI infrastructure engineering within Amazon ’s ecosystem. 📊 Role Difficulty: Medium | Competition Level: High | Fresher Friendly: No NexisGrow.com features this opportunity as part of its curated tech job listings. All details are sourced from the official job posting. Apply online before the opportunity closes. Data Engineer II, Alexa AI - ML Engineering jobs Amazon recruitment apply online Bengaluru, KA, India jobs Job Role & Responsibilities The Data Engineer II, Alexa AI - ML Engineering role at Amazon ensures reliable data flow for Alexa AI by building scalable ETL pipelines and maintaining data warehousing structures that support real-time model training and user behavior analysis. Build and deploy ETL pipelines using Apache Airflow or Spark to extract user interaction data from device logs and transform it into structured formats for machine learning models. Utilize SQL to design and implement data modeling schemas that support efficient querying of user session data and device telemetry in Amazon Redshift . Collaborate with ML engineering teams to integrate data warehousing outputs into TensorFlow or PyTorch training pipelines, ensuring data consistency and feature availability. Monitor data performance metrics such as latency , throughput , and error rates in Amazon CloudWatch to detect anomalies in ETL pipeline execution. Maintain and update existing data infrastructure codebases using Git and CI/CD workflows to ensure stability and reproducibility of data processing jobs. Document data modeling decisions, ETL pipeline configurations, and data quality checks in Confluence or Notion to enable onboarding and audit trails. Identify and resolve data-related issues such as schema drift or missing fields in Amazon S3 datasets that impact model training accuracy and performance. Support production data warehousing operations by validating SQL queries against Redshift and ensuring compliance with data lineage standards. This role demands direct ownership of data infrastructure and ETL pipeline reliability, with every change impacting model performance and user experience in Amazon Alexa services. Required Skills & Technical Competencies The role requires a strong foundation in SQL , data modeling , ETL pipelines , and data warehousing to manage large-scale data flows in Amazon Alexa AI systems. Technical Skills SQL — advanced — used to write complex queries for data extraction, transformation, and validation in Amazon Redshift and S3 datasets. Data modeling — intermediate to advanced — applied to design normalized and denormalized schemas for user behavior and device telemetry data in data warehousing environments. ETL pipelines — advanced — implemented using Apache Airflow and Spark to extract, transform, and load data from device logs into data lakes and warehouses . Data warehousing and modeling — intermediate to advanced — used to organize and structure data for analytics, ensuring efficient query performance and scalability in Amazon Redshift . When showcasing these technical skills, emphasize real-world projects involving SQL queries, ETL pipeline design, and data modeling in production environments with measurable outcomes. Eligibility Criteria This role is designed for candidates with 4+ years of hands-on data engineering experience and a technical qualification in computer science, data engineering, or a related field. Must hold a degree in Computer Science , Electrical Engineering , or a related technical discipline. Eligible batches are 2023 , 2024 , 2025 , and 2026 only. Minimum of 4 years of hands-on experience in data engineering , including SQL and ETL pipeline development. CGPA or academic performance is not specified, but relevant technical projects must be demonstrable. Must have a portfolio showcasing SQL queries, data modeling designs, and ETL pipeline implementations with clear technical outcomes. Experience with data warehousing tools such as Amazon Redshift or Google BigQuery is required for eligibility. Documentation & Portfolio Requirements Your resume must include a technical portfolio with specific examples of SQL queries, data modeling diagrams, and ETL pipeline configurations used in real projects. For this role, prioritize including a GitHub link with SQL scripts, data modeling schemas, and ETL pipeline code in Apache Airflow or Spark — clearly labeled and documented with performance metrics or data volume handled. Salary for Data Engineer II, Alexa AI - ML Engineering at Amazon 💰 Compensation Not Disclosed The advertised compensation for the Data Engineer II, Alexa AI - ML Engineering role at Amazon is Not Disclosed . The exact in-hand figure and any additional components are confirmed by the company during the offer or HR discussion stage. Recommended Courses & Preparation Tips for Data Engineer II, Alexa AI - ML Engineering Upskilling with the right resources significantly enhances your chances of selection for this role by ensuring you meet the technical requirements and industry standards. Recommended Courses & Resources SQL — Mastering SQL is crucial for data manipulation and querying in this role. KodNest — This platform offers hands-on projects that enhance your data engineering skills. Boost your profile with relevant certifications at NexisGrow GetCertified — strengthen your application before you apply. Common Mistakes to Avoid ❌ Applying without demonstrating 4+ years of SQL experience — Ensure to provide specific examples. ❌ Using a generic resume — Tailor it to highlight relevant experience in data engineering. ❌ Listing SQL and ETL skills without detailing application — Clearly state where these skills were applied in past roles. ❌ Ignoring the experience requirement — Avoid applying as a fresher for this role. ❌ Adding unrelated technologies or unsupported claims — Stick to relevant skills and experiences. ❌ Failing to verify job details on the official Apply URL — Always check before submission. Before You Apply — Checklist ✅ Confirm the job title, company, location, work mode, and experience requirement. ✅ Check that you meet the supplied qualification criteria. ✅ Verify eligibility against the supplied eligible batches and experience requirement. ✅ Add relevant supplied JD keywords naturally to your resume. ✅ Highlight projects or experience related to the supplied technologies and responsibilities. ✅ Remove unsupported technologies, achievements, or experience claims. ✅ Open and verify the supplied Apply URL before submitting the application. ✅ Save the job details, application date, and role-specific resume version for tracking. Resume Tailoring & ATS Keywords for Data Engineer II, Alexa AI - ML Engineering Optimizing your resume for ATS is crucial for ensuring it passes initial screenings and reaches hiring managers. ATS Keywords to Include SQL data modeling ETL pipelines data engineering warehousing data quality collaboration monitoring troubleshooting documentation support performance Resume Tips for This Role Highlight your 4+ years of SQL experience prominently on your resume. Emphasize your experience with data modeling and ETL pipelines , as these are critical for the role. Include any relevant projects that demonstrate your skills in SQL and data engineering. Use exact keywords from the job description naturally in your resume to align with ATS requirements. Avoid adding unsupported claims or technologies that you cannot substantiate with experience. Build an ATS-optimized resume for this role using NexisGrow Resume Builder — free for all job seekers. Pro Tip: Do not include unrelated work experience or unsupported technologies in your resume for this role. How to Apply for Data Engineer II, Alexa AI - ML Engineering at Amazon Apply Now — Amazon Open the official Apply URL and confirm the job title and company matches " Data Engineer II, Alexa AI - ML Engineering " at Amazon . Prepare a resume that aligns with the required skills, responsibilities, qualifications, and experience for the role. Complete the official application form accurately, ensuring all information is truthful and avoiding unsupported claims. Submit the application and save the confirmation or application reference number if provided by the portal. Record the application date and monitor the official company portal or registered email for updates. Applications are reviewed on a rolling basis — early submission is recommended. Apply Now — Amazon NexisGrow.com does not charge any fees for job applications. Amazon Amazon is a technology company based in Bengaluru, KA, India . This Data Engineer II, Alexa AI - ML Engineering role operates in an onsite work mode and supports Amazon 's AI and machine learning initiatives in the technology industry. The team works on enhancing data quality and processing capabilities through data modeling , warehousing , and ETL pipelines . They collaborate with engineers and stakeholders to build robust data systems that power Alexa AI. This role provides early-career exposure to advanced data engineering practices, including SQL , data modeling , and ETL pipelines —key technologies used in machine learning environments at Amazon . Company Details Industry Technology Location Bengaluru, KA, India Connect With Us Careers Apply Now Website 🔗 amazon.jobs Frequently Asked Questions Interview · Role · Salary · Growth ? Who can apply for this role? Eligibility Tap to expand + Answer Candidates with a relevant technical qualification and 4+ years of experience in data engineering can apply. ? What technical skills are most important for this role? Skills Tap to expand + Answer SQL, data modeling, ETL pipelines, and data warehousing are the most important skills for this role. ? What is the expected salary for this position? Salary Tap to expand + Answer The expected salary is 'Not Disclosed' as per the job posting. ? What should I expect after applying? Hiring Process Tap to expand + Answer The exact hiring stages are not specified in the job posting. ? How should I prepare for the interview? Preparation Tap to expand + Answer Review SQL and data modeling concepts, practice building ETL pipelines, prepare to discuss past data engineering projects, familiarize yourself with data quality metrics, and understand the role of data in machine learning. ? Is this role remote, hybrid, or onsite? Work Mode Tap to expand + Answer This role is onsite in Bengaluru, KA, India. ? What career exposure can this role provide? Growth Tap to expand + Answer The role offers exposure to advanced data engineering practices and collaboration with engineering teams, enhancing skills in SQL and ETL processes. ? What should I highlight in my resume for this role? Resume Tap to expand + Answer Highlight your SQL experience, data modeling skills, ETL pipeline projects, and relevant technical qualifications. ? Is there a last date to apply? Application Tap to expand + Answer Not specified in the job posting. ? Is there a probation period? Probation Tap to expand + Answer Not specified in the job posting. ? What is the work environment like for this role? Culture Tap to expand + Answer The role involves collaboration with engineers and stakeholders to enhance data quality and processing capabilities. ? Can freshers apply for this role? Fresher Tap to expand + Answer No, this role requires 4+ years of experience, making it unsuitable for freshers. 🔗 Explore More on NexisGrow More jobs in Bengaluru Browse all Tech jobs Latest Fresher jobs More jobs at Amazon Work From Home jobs Ready to Apply? Don't Miss This Opportunity! Apply only via the official link. NexisGrow.com charges zero application fees. 👉 Apply Now — Official Link NexisGrow.com does not charge any application or registration fees. Beware of fraudulent offers. Naukri ki baat, NexisGrow ke saath • NexisGrow.com