Merck (EMD Group) is Hiring Software Engineer — Data Platform Engineering | Bangalore | 0 - 2 Years

Job Description

This Software Engineer opening — from the global science and technology company operating in Healthcare, Life Science, and Electronics (known as Merck KGaA/EMD Group outside the US and Canada) — is a genuinely well-rounded fresher opportunity worth flagging for its 𝐦𝐨𝐝𝐞𝐫𝐧 𝐜𝐥𝐨𝐮𝐝 𝐢𝐧𝐟𝐫𝐚𝐬𝐭𝐫𝐮𝐜𝐭𝐮𝐫𝐞 focus combined with explicit, structured 𝐀𝐈-𝐭𝐨𝐨𝐥 𝐢𝐧𝐭𝐞𝐠𝐫𝐚𝐭𝐢𝐨𝐧 into daily engineering work. This is one of the more forward-looking listings covered on this site regarding AI: rather than just listing "AI awareness" as a preferred skill, the posting explicitly states interns will use AI tools "from day one" across code generation, debugging, documentation, and exploratory analysis as a normal part of the engineering workflow — genuinely useful context for how modern data platform teams are actually integrating AI into daily practice, not just talking about it.

The role sits within 𝐃𝐚𝐭𝐚 𝐏𝐥𝐚𝐭𝐟𝐨𝐫𝐦 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠, building infrastructure that lets the broader organization discover, publish, and govern data products at scale — this is foundational data infrastructure work rather than building customer-facing features or analytics dashboards directly. For candidates interested in 𝐩𝐥𝐚𝐭𝐟𝐨𝐫𝐦/𝐢𝐧𝐟𝐫𝐚𝐬𝐭𝐫𝐮𝐜𝐭𝐮𝐫𝐞 𝐞𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠 specifically, this is a genuinely solid, well-scoped entry point.

The technical requirements span a comprehensive but clearly explained 𝐀𝐖𝐒 𝐞𝐜𝐨𝐬𝐲𝐬𝐭𝐞𝐦 — 𝐄𝐊𝐒 (𝐊𝐮𝐛𝐞𝐫𝐧𝐞𝐭𝐞𝐬), 𝐑𝐃𝐒, 𝐒𝟑, 𝐆𝐥𝐮𝐞, 𝐈𝐀𝐌, 𝐕𝐏𝐂, and 𝐂𝐥𝐨𝐮𝐝𝐅𝐫𝐨𝐧𝐭 — alongside 𝐏𝐲𝐭𝐡𝐨𝐧 development and infrastructure-as-code tooling (𝐓𝐞𝐫𝐫𝐚𝐟𝐨𝐫𝐦/𝐂𝐥𝐨𝐮𝐝𝐅𝐨𝐫𝐦𝐚𝐭𝐢𝐨𝐧). This is a real, substantial cloud infrastructure skill set for a fresher role, though the listing frames much of it as "working knowledge" rather than deep expertise, making it a reasonable target for candidates who've done coursework or personal projects touching AWS fundamentals rather than requiring production-level cloud engineering experience already.

Our Take:

- 𝐆𝐨𝐨𝐝 𝐟𝐨𝐫: CS/IT graduates with genuine Python proficiency and some AWS/cloud fundamentals exposure (even from personal projects or certifications), who are comfortable actively using AI coding tools as part of daily workflow and interested in data infrastructure/platform engineering specifically

- 𝐍𝐨𝐭 𝐢𝐝𝐞𝐚𝐥 𝐟𝐨𝐫: those with zero cloud computing exposure or purely application-development-focused backgrounds without any infrastructure interest — the AWS service breadth here is genuinely substantial

- 𝐒𝐞𝐥𝐞𝐜𝐭𝐢𝐨𝐧 𝐝𝐢𝐟𝐟𝐢𝐜𝐮𝐥𝐭𝐲: moderate — the core requirements (Python, REST APIs, basic AWS knowledge) are achievable for CS freshers with some self-study, and the listing's explicit "0-2 years... or equivalent practical experience" framing suggests genuine openness to strong self-taught candidates

- 𝐂𝐚𝐫𝐞𝐞𝐫 𝐭𝐫𝐚𝐣𝐞𝐜𝐭𝐨𝐫𝐲: commonly leads into Senior Software Engineer, Data Platform Engineer, or Cloud Infrastructure Engineer roles, with genuine AWS and data governance platform experience being valuable for future roles at any company building modern data infrastructure

Compensation Context: No compensation figure is disclosed in this posting. Software Engineer roles in data platform/infrastructure engineering at large global science and technology companies in Bangalore typically range around ₹𝟕–𝟏𝟎 𝐋𝐏𝐀 for freshers with solid Python and cloud fundamentals, based on general market data for comparable entry-level cloud/platform engineering roles — this is an estimate only.

Application Strategy: Given the substantial AWS service list, don't expect to have deep expertise in all of them — instead, build genuine familiarity with the core few (𝐒𝟑, 𝐈𝐀𝐌, and either 𝐄𝐊𝐒 or basic 𝐓𝐞𝐫𝐫𝐚𝐟𝐨𝐫𝐦) through a personal project or AWS free-tier experimentation, and be ready to discuss it specifically; separately, since the listing explicitly and repeatedly emphasizes active AI tool usage as part of the role, be prepared to discuss how you've used 𝐀𝐈 𝐜𝐨𝐝𝐢𝐧𝐠 𝐚𝐬𝐬𝐢𝐬𝐭𝐚𝐧𝐭𝐬 in your own projects — not just "I've used ChatGPT," but specific examples of how it changed your workflow or helped you debug something concrete.

Roles & Responsibilities

The role blends hands-on Python development with cloud infrastructure management — a genuinely full-stack platform engineering scope rather than narrowly focused on just one layer.

- Contribute to Python-based data integration workflows

- Help maintain and improve CI/CD pipelines

- Write infrastructure-as-code to provision and manage AWS cloud resources

- Participate in code reviews and architecture discussions

- Collaborate with data product teams and platform stakeholders

- Support platform reliability and developer experience

- Actively use AI tools throughout the engineering workflow, including code generation, debugging, and documentation

Qualifications & Eligibility

Genuinely open framing — explicitly accepts equivalent practical experience alongside a formal degree.

- 0–2 years of experience

- Bachelor's degree in Computer Science, IT, Engineering, or a related field, or equivalent practical experience

Skills Required

A substantial but clearly scoped technical list, blending core programming with cloud infrastructure and modern AI-tool fluency.

- Clean, maintainable Python and REST API experience; familiarity with Java/Spring is a plus

- Working knowledge of core AWS services, including EKS, RDS, S3, Glue, IAM, VPC, and CloudFront

- Exposure to infrastructure-as-code tools such as Terraform or CloudFormation

- Familiarity with Git branching, pull requests, code reviews, and CI/CD concepts

- Comfort with the command line, basic shell scripting, and Linux troubleshooting

- Understanding of AI/LLM concepts, practical applications, and ethical considerations

- Welcome additions: Experience with Kubernetes, containerized deployments, data governance platforms, or Agile methodologies