Associalte Specialist , Data Engineering

Merck Gruppe - MSD Sharp & Dohme; Hyderabad; Hybrid; INR 1,200,000 - 1,800,000; Full time

Job summary

Merck Gruppe - MSD Sharp & Dohme in Hyderabad is seeking a Data Engineer with 2–4 years of hands-on experience to design, build, and maintain data pipelines and analytics-ready datasets. The role emphasizes Python, PySpark, SQL, AWS, and Databricks, with cloud and CI/CD practices, data quality, and production support.

You will collaborate with Data Analysts, Scientists, and product teams, operate in a hybrid onsite/remote model, and contribute to scalable data solutions while growing ownership

Qualifications

• Bachelor’s degree in computer science, Engineering, or related field, or equivalent practical experience.
• 2–4 years of hands-on data engineering experience building/maintaining production data pipelines.
• Hands-on with AWS services (S3, Glue, Lambda, Step Functions, EMR, CloudWatch) and security basics.
• Experience with Databricks, Apache Spark, PySpark, and Delta Lake concepts.
• Strong SQL skills for profiling, transformations, and performance tuning.
• Working knowledge of Python and PySpark, with cloud and CI/CD familiarity.
• Understanding of dimensional modeling, star/snowflake schemas, and SCD.
• Exposure to GitHub, CI/CD, code reviews, branching, and deployment practices.
• Docker and Terraform for deployment and cloud environment support.

Responsibilities

• Build, enhance, and support batch and streaming data pipelines.
• Develop and maintain ETL/ELT transformations across data lake, lakehouse, and warehouse environments.
• Collaborate with Analysts, Scientists, engineers, and product managers to deliver analytics-ready datasets.
• Implement data quality checks and basic anomaly checks to improve data trust.
• Run, monitor, and troubleshoot pipelines using Databricks Workflows, AWS Step Functions, and related tools.
• Follow CI/CD practices with unit/integration testing and automated data tests.
• Support BI use cases with dimensional modeling concepts and SCDs.
• Write and optimize SQL queries for data profiling, transformations, and validation.
• Utilize AWS services (S3, Glue, Lambda, Step Functions, EMR) and Terraform/Docker for deployment.
• Contribute to cloud resource provisioning and environment configuration under guidance.

Skills

Python

PySpark

SQL

AWS

Databricks

GitHub

CI/CD

Data Lake

ETL/ELT

Apache Spark

Delta Lake

Docker

Terraform

Education

Bachelor’s degree in computer science or engineering

Tools

Databricks

AWS

Docker

Terraform

GitHub

Job description

Job Description

Associate Specialist: Data Engineering

The Opportunity:

Join a global biopharma company with a 130-year legacy and mission to achieve new milestones in healthcare. Be part of a technology-driven, data-led organization supporting a diversified portfolio of medicines, vaccines, and animal health products. Work alongside passionate teams that use data, analytics, and insights to drive decisions and tackle some of the world’s greatest health threats.

Our Technology Centers are globally distributed hubs that enable our digital transformation and business outcomes across IT. They bring together diverse teams to collaborate, share best practices, and deliver solutions that save and improve lives.

This role is based at our Hyderabad Tech Center and follows a hybrid working model (3 days onsite, 2 days remote). Candidates are expected to reside within commuting distance of the Hyderabad office.

Role Overview

We are looking for a Data Engineer with 2–4 years of hands‑on experience in building and supporting data pipelines, ETL/ELT workflows, and analytics‑ready datasets. The ideal candidate should have strong fundamentals in Python, PySpark, SQL, AWS, and Databricks, with practical exposure to data lakes, lakehouse patterns, data warehousing, data quality, and production support. This role is best suited for a hands‑on engineer who can work from defined requirements, contribute to reliable data solutions, collaborate with cross‑functional teams, and grow into larger ownership over time.

What will you do in this role

• Build, enhance, and support batch and streaming data pipelines using defined technical designs and backlog requirements.

• Develop and maintain ETL/ELT transformations using Python, PySpark, and SQL across data lake, lakehouse, and warehouse environments.

• Work closely with Data Analysts, Data Scientists, senior engineers, tech leads, and product managers to understand requirements and deliver curated, analytics‑ready datasets.

• Implement data quality checks, validations, reconciliations, and basic anomaly checks to improve trust and usability of data outputs.

• Run, monitor, and troubleshoot pipelines using orchestration and observability tools such as Databricks Workflows, AWS Step Functions, scheduling, logging, monitoring, and alerting.

• Follow engineering practices including unit testing, integration testing, automated data tests, code reviews, and quality gates within CI/CD.

• Support BI and analytics use cases by applying dimensional modeling concepts such as facts, dimensions, star/snowflake schemas, and slowly changing dimensions (SCD).

• Write and tune SQL queries for data profiling, transformations, validations, debugging, and performance improvements.

• Use AWS services such as S3, Glue, Lambda, Step Functions, EMR, and CloudWatch to support data engineering workloads while following security practices such as IAM, encryption, and least privilege.

• Contribute to cloud resource provisioning and environment configuration using Terraform, with guidance from senior engineers.

• Package, deploy, and support workloads using Docker and related runtime configurations, including ECS/Fargate where applicable.

• Use GitHub for version control, branching, pull requests, code reviews, and contribution to CI/CD pipelines.

• Develop scalable data processing logic on Databricks / Apache Spark using PySpark and lakehouse concepts such as Delta Lake, ACID transactions, and schema evolution.

• Use Jupyter/Databricks notebooks for exploration, debugging, and PoCs; convert validated logic into reusable modules, tests, and deployment‑ready pipelines.

• Participate in Agile delivery ceremonies, provide task‑level estimates, share progress updates, and raise risks or dependencies early.

• Create and maintain technical documentation such as pipeline specifications, data contracts, runbooks, and support notes.

What Should you have:

• Bachelor’s degree in computer science, Engineering, or a related field, or equivalent practical experience.

• 2–4 years of hands‑on experience in data engineering, including building or supporting production data pipelines and ETL/ELT workflows.

• Practical experience with AWS services such as S3, Glue, Lambda, Step Functions, EMR, and CloudWatch; understanding of IAM, encryption, and cloud security basics.

• Hands‑on experience with Databricks, Apache Spark, PySpark, and lakehouse concepts such as Delta Lake.

• Strong SQL skills for joins, window functions, data profiling, transformations, validations, and performance tuning.

• Good working knowledge of Python and PySpark, including Spark fundamentals such as partitioning, shuffle, caching, file formats, debugging, and optimization.

• Understanding of dimensional modeling concepts including facts, dimensions, star/snowflake schemas, and slowly changing dimensions (SCD).

• Exposure to GitHub, CI/CD, code reviews, branching, release practices, and engineering quality standards.

• Working knowledge of Docker and Terraform for deployment, runtime configuration, and cloud environment support.

• Ability to work in Agile teams, communicate clearly, collaborate with cross‑functional stakeholders, and take ownership of assigned deliverables.

Primary Skills:

Python, PySpark, SQL, AWS, Databricks, GitHub, Data Lake, ETL/ELT and CI/CD

Secondary Skills:

Dimensional modeling, Docker and Terraform

Good to Have

• Exposure to data quality or testing frameworks such as Collibra, Immuta, and basic awareness of data governance practices including catalog, lineage, and access controls.

• Exposure to orchestration tools such as Airflow or modern table formats such as Delta, Iceberg.

• AWS certification such as Developer or Solutions Architect, or equivalent demonstrated cloud experience.

Who we are

We are known as well‑known org Inc., Rahway, New Jersey, USA in the United States and Canada and MSD everywhere else. For more than a century, bringing forward medicines and vaccines for many of the world's most challenging diseases. Today, our company continues to be at the forefront of research to deliver innovative health solutions and advance the prevention and treatment of diseases that threaten people and animals around the world.

What we look for

Imagine getting up in the morning for a job as important as helping to save and improve lives around the world. Here, you have that opportunity. You can put your empathy, creativity, digital mastery, or scientific genius to work in collaboration with a diverse group of colleagues who pursue and bring hope to countless people who are battling some of the most challenging diseases of our time. Our team is constantly evolving, so if you are among the intellectually curious, join us—and start making your impact today.

Required Skills:

Amazon Web Services (AWS), CI/CD, Databricks Platform, Data ETL, Data Lake, GitHub, PySpark, Python (Programming Language), SQL Databases

Preferred Skills:

Dimensional Modeling, Docker (Software), Terraform

Secondary Language(s) Job Description:

#MSDHYDIT

Job Posting End Date:

09/16/2026

*A job posting is effective until 11:59:59PM on the day BEFORE the listed job posting end date. Please ensure you apply to a job posting no later than the day BEFORE the job posting end date.

Requisition ID:

R414161

Employee Status: Regular

Relocation: Domestic

VISA Sponsorship: No

Travel Requirements: No Travel Required

Flexible Work Arrangements: Hybrid

Shift: Not Indicated

Valid Driving License: No

Hazardous Material(s): n/a