Senior Analyst, Data Design and Engineering

Location: Bengaluru

At Johnson & Johnson, we believe health is everything. Our strength in healthcare innovation empowers us to build a world where complex diseases are prevented, treated, and cured, where treatments are smarter and less invasive, and solutions are personal. Through our expertise in Innovative Medicine and Med Tech, we are uniquely positioned to innovate across the full spectrum of healthcare solutions today to deliver the breakthroughs of tomorrow, and profoundly impact health for humanity. Learn

more at

Job Function

Data Analytics & Computational Sciences

Job Sub Function

Data Engineering

Job Category

Scientific/Technology

All Job Posting Locations:

Bangalore, Karnataka, India, Bogotá, Distrito Capital, Colombia, Paranaque, National Capital Region (Manila), Philippines

Job Description

This role reports to the Data and Digital Manager within the Data Transformation & Business Intelligence (DTBI) team of the Data, Digital and AI (DDAI) organization. The DTBI team provides data-transformation tools and services, process management and governance, and develops analytics tools and automated processes across JNJ Global Services.

The Data Design and Engineering Senior Analyst will be responsible for creating and delivering sophisticated workflows in our modernized GS Data Analytics Platform (GSIE), Databricks, Alteryx/Dataiku, and other business ETL tools. The analyst will design, enrich, and optimize the data-pipeline architecture, as well as improve data flows and data collection across functions. The analyst will work closely with other technical and business solution architects, data engineers, data modelers, data architects, testers, visualization analysts, reporting and data-science teams, and business leaders to execute strategic priorities and ensure consistent, efficient data-delivery designs across projects.

Major

Duties & Responsibilities

Develop and maintain workflows, transformation designs, and integration activities for the GS Enterprise Data Lake & Analytics Platform (GSIE).
Establish and enforce industry standards and best practices for data engineering across new and existing projects and datasets.
Work independently and collaboratively with data professionals, analytics specialists, and technical and business leaders to gather functional and non-functional requirements, assemble large, sophisticated datasets, and ensure system functionality.
Create and maintain standardized governance for data modeling and transformation by defining and refining data relationships and structures (conceptual, logical, and physical models).
Understand and maintain data lineage, metadata, and relationships.
Ensure the Entity Relationship Diagram (ERD) is kept up to date.
Identify, design, and implement internal process improvements — for example, automating manual processes, optimizing data delivery, and redesigning infrastructure for greater scalability.
Build infrastructure for optimal extraction, transformation, and loading (ETL) from diverse data sources.
Build analytics tools that leverage the data pipeline to deliver insights into customer experience, operational efficiency, and process effectiveness.
Create data-modeling assets for visualization analysts and data scientists to support the development of effective and innovative data products.
Contribute creative and innovative ideas to user-experience and technical design discussions.
Develop and provide documentation, training, and support as requirements emerge.
Perform other work-related duties as assigned.

Qualifications

Required education:
Bachelor's degree (4-year) in a STEM field, preferably Information Technology, Computer Science, or Management Information Systems/Technology.
Intermediate to advanced SQL scripting skills and experience working with relational databases and/or data lakes such as Databricks (preferred), Snowflake, Postgre

SQL, and Oracle.
Advanced experience in schema design and a deep understanding of star schema, entity-attribute modeling, dimensional modeling, metadata design, data dictionaries, and overall data governance.
Intermediate to advanced Python skills (PySpark preferred) for building and optimizing big-data pipelines,…