Sr. Specialist, Data Engineering

Merck; Hyderabad; On-site; INR 2,000,000 - 3,500,000; Full time

Job summary

Merck in Hyderabad is seeking a Data Engineer to design, build and maintain scalable data pipelines and platforms. You will partner with data scientists, analysts and business stakeholders to translate requirements into production-grade datasets and pipelines.

The role emphasizes automation, monitoring, and governance across cloud data warehouses. You will work within a matrix environment and contribute to project planning, data ingestion, and reporting while leveraging AWS and Databricks

Qualifications

• Bachelor’s degree in IT, CS or related tech stream.
• 7–11 years in data pipelines and data infrastructure, preferably with life sciences context.
• Strong SQL and Python (incl. PySpark) skills; cloud and data warehouse experience.
• Hands-on with Spark, Databricks, and cloud object storage; CI/CD for data deployments.

Responsibilities

• Design, build and maintain scalable data pipelines and platforms.
• Collaborate with data scientists, analysts and business stakeholders to translate requirements.
• Develop pipelines to ingest data into cloud data warehouses and data lakes.
• Automate data flows, monitoring, logging and data quality checks.
• Maintain documentation for integration processes and code for scalability.
• Deliver standard reports and support cross‑team project planning.

Skills

Python

SQL

PySpark

AWS

Data Modelling

ETL

CI/CD

Data governance

Communication

Education

Bachelors in IT/CS

Tools

Apache Spark

Databricks

AWS (S3, IAM)

Delta Lake

Redshift / Snowflake

GitHub Actions

Jenkins

Azure DevOps

Job description

Based in Hyderabad, join a global healthcare biopharma company and be part of a 130- year legacy of success backed by ethical integrity, forward momentum, and an inspiring mission to achieve new milestones in global healthcare.

Be part of an organisation driven by digital technology and data-backed approaches that support a diversified portfolio of prescription medicines, vaccines, and animal health products.

Drive innovation and execution excellence. Be a part of a team with passion for using data, analytics, and insights to drive decision-making, and which creates custom software, allowing us to tackle some of the world's greatest health threats.

Our Technology Centers focus on creating a space where teams can come together to deliver business solutions that save and improve lives. An integral part of our company's IT operating model, Tech Centers are globally distributed locations where each IT division has employees to enable our digital transformation journey and drive business outcomes. These locations, in addition to the other sites, are essential to supporting our business and strategy.

A focused group of leaders in each Tech Center helps to ensure we can manage and improve each location, from investing in growth, success, and well-being of our people, to making sure colleagues from each IT division feel a sense of belonging to managing critical emergencies. And together, we must leverage the strength of our team to collaborate globally to optimize connections and share best practices across the Tech Centers.

Role Overview

As a Data Engineer, you will design, build and maintain scalable data pipelines and platforms and ensure pipeline reliability, performance and governance through automation, monitoring, logging and documentation. You will partner with data scientists, analysts and business stakeholders to translate requirements into production‑grade, observable pipelines and datasets. You will operate within a matrix environment, participating in project planning, delivery and cross‑team collaboration.

What will you do in this role:

• Design, develop, and maintain data pipelines to extract data from various sources and populate a data lake and data warehouse.
• Work closely with data scientists, analysts, and business teams to understand data requirements and deliver solutions aligned with business goals.
• Build and maintain platforms that support data ingestion, transformation, and orchestration across various data sources, both internal and external.
• Use data orchestration, logging, and monitoring tools to build resilient pipelines.
• Automate data flows and pipeline monitoring to ensure scalability, performance, and resilience of the platform.
• Monitor, troubleshoot, and resolve issues related to the data integration platform, ensuring uptime and reliability.
• Maintain thorough documentation for integration processes, configurations, and code to ensure easy onboarding for new team members and future scalability.
• Develop pipelines to ingest data into cloud data warehouses.
• Create and deliver standard reports in accordance with stakeholder needs.
• Work within a matrix organizational structure, reporting to both the functional manager and the project manager.
• Participate in project planning, execution, and delivery, ensuring alignment with both functional and project goals.

What should you have:

• Primary: (Python, SQL, PySpark, AWS, Apache Spark, Databricks, cloud object storage, ci/cd, ETL, data modelling)
• Bachelors' degree in Information Technology, Computer Science or any Technology stream.
• 7-11 years of experience in developing data pipelines & data infrastructure, ideally within a drug development or life sciences context.
• Strong SQL skills and solid programming experience in Python (including PySpark)
• Practical experience with AWS S3 and core AWS console concepts (IAM, regions, basic cloud architecture)
• Hands‑on experience with Apache Spark (concepts and usage) and Databricks (platform use, Delta Lake, Unity Catalog)
• Experience with cloud object storage (e.g., Amazon S3) and cloud data warehouses or lakehouses (e.g., Redshift, Snowflake, Azure Synapse, Delta Lake)
• Familiarity with data modeling, ETL/ELT patterns, and data transformation best practices
• Experience implementing monitoring, logging, and data quality checks for operational pipelines
• Familiarity with CI/CD concepts and pipelines for data deployments, experience with Git‑based tooling (GitHub Actions, Jenkins, or Azure DevOps)
• Proven ability to work collaboratively with data scientists, analysts, and business stakeholders
• Good interpersonal and communication skills (verbal and written)
• Product and customer‑centric approach and innovative thinking

Secondary skills (nice to have) :

• Experience with AI Assisted code development, GitHub Copilot, people management, and team lead experience
• Prior experience in a global or matrixed organization
• Exposure to observability and data quality platforms (Monte C