Software Engineer (Data & AI)

Candidates typically face a timed online coding test followed by a deep‑dive technical interview covering data pipeline design, cloud services and AI fundamentals. The HR round focuses on cultural fit, teamwork experiences and career aspirations. Preparation should include hands‑on projects with Snowflake or AWS and clear articulation of past project impact.

Merck fosters an inclusive, science‑driven environment where employees are encouraged to experiment and collaborate across borders. The company offers structured career growth, mentorship programs, and a healthy work‑life balance supported by flexible working arrangements and wellness initiatives.

Bachelor's or Master's degree in Computer Science, Information Technology, Electronics, or related engineering discipline; minimum 60% aggregate (or CGPA 6.0/10); graduating batch 2024‑2026; no active backlogs at the time of joining; strong academic record in programming, data structures and algorithms; fluency in English (both written and spoken).

Round 1: Online coding assessment (data structures, algorithms, SQL) → Round 2: Technical interview (system design, data pipelines, AI concepts) → Round 3: HR interview (cultural fit, motivations, compensation discussion)

Merck Group, a global leader in science and technology, has a legacy of more than 350 years in delivering innovative solutions across Healthcare, Life Science, and Electronics. With a presence in over 60 countries, the company combines deep scientific expertise with cutting‑edge digital capabilities to improve the lives of patients, customers, and communities worldwide. In India, Merck operates state‑of‑the‑art research centres, manufacturing hubs and a growing digital ecosystem that supports its mission of "Sparking Discovery and Elevating Humanity". The culture emphasizes curiosity, inclusion, and a relentless focus on ethical innovation, making it an attractive destination for fresh talent eager to make a tangible impact. The role of Software Engineer (Data & AI) sits within the Enabling Functions Data Office, a product‑oriented delivery unit that builds data‑driven platforms for HR, procurement, legal and other core functions. As a member of an internationally distributed pod, you will translate complex business problems into scalable data pipelines, AI‑enabled services and intuitive user interfaces. You will own end‑to‑end delivery – from architecture and coding to testing, deployment and monitoring – while ensuring compliance with governance, security and cost‑efficiency standards. Key Responsibilities: 1. Design, develop and maintain robust data pipelines using PySpark, Snowflake and Palantir Foundry. 2. Build AI‑powered micro‑services that automate manual workflows across Enabling Functions. 3. Implement CI/CD pipelines and automated testing frameworks for both data and AI components. 4. Ensure data lineage, governance, privacy and security controls are embedded in all solutions. 5. Collaborate with product owners, business analysts and domain experts to capture requirements and translate them into technical specifications. 6. Optimize cloud resources on AWS to achieve cost‑effective scalability. 7. Participate in code reviews, knowledge‑sharing sessions and mentorship of junior engineers. 8. Contribute to the evolution of the data engineering practice, defining standards and best practices. 9. Support the Spain‑based hub by coordinating cross‑regional deliverables and aligning on global AI use‑cases. 10. Stay abreast of emerging AI/ML technologies and propose innovative use‑cases such as carbon‑footprint analytics and procurement intelligence. Tech Stack: Python, PySpark, Spark, Snowflake, Palantir Foundry, AWS (S3, Lambda, Glue), Git, Docker, Kubernetes, CI/CD tools (Jenkins/GitHub Actions), MLOps basics. Growth Path: Starting as a Software Engineer, you can progress to Senior Engineer, Lead Engineer, and eventually Data Platform Architect or AI Product Manager, with opportunities to move across functional domains or geographies. Why Join Merck? You will work on enterprise‑scale AI projects that directly influence the efficiency of a multinational corporation, gain exposure to world‑class data platforms, and be part of a culture that values scientific rigor, ethical AI, and personal development. The role offers a blend of technical challenge, global collaboration, and a purpose‑driven mission that resonates with ambitious fresh graduates.