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Job Function:

Marketing

Job Sub Function:

Marketing Insights & Analytics

Job Category:

Professional

All Job Posting Locations:

Pune, Maharashtra, India

Job Description:

Associate Lead – Pricing (Data Engineer)

Location: Pune

Reports to: DS Commercial Strategy & Insights Team

Johnson & Johnson announced plans to separate our Orthopaedics business to establish a standalone orthopaedics company, operating as DePuy Synthes. The process of the planned separation is anticipated to be completed by June 2027, subject to legal requirements, including consultation with works councils and other employee representative bodies, as may be required, regulatory approvals and other customary conditions and approvals.

Should you accept this position, it is anticipated that, following conclusion of the transaction, you would be an employee of DePuy Synthes and your employment would be governed by DePuy Synthes employment processes, programs, policies, and benefit plans. In that case, details of any planned changes would be provided to you by DePuy Synthes at an appropriate time and subject to any necessary consultation processes.

  

Responsibilities & Scope

Johnson & Johnson is recruiting for Global DS Commercial Strategy & Insights Team, an experienced Data Engineer Lead / Architect to design, develop, migrate, and optimize scalable data pipelines and warehouse solutions. The role requires advanced SQL and Python expertise, strong knowledge of data architecture and ETL frameworks, and hands-on experience with Amazon Redshift. The individual will provide technical leadership and ensure data solutions are reliable, secure, high-performing, and ready for analytics and reporting.

Key Responsibilities

 

• Design and develop scalable SQL- and Python-based ETL/ELT pipelines.
• Build Python scripts and reusable modules for data ingestion, transformation, validation, automation, and monitoring.
• Define pipeline architecture covering partitioning, incremental loads, change data capture, job dependencies, and error handling.
• Prepare pipeline designs, source-to-target migration mappings, transformation specifications, and reconciliation logic.
• Analyse query execution plans and optimize complex SQL queries, Python processes, and ETL performance.
• Implement CI/CD practices for data pipelines, Python code, SQL code, and environment-aware deployments.
• Apply secure authentication and secrets-management patterns, including service accounts.
• Lead technical design reviews, troubleshooting, documentation, and engineering best practices.
• Collaborate with analytics, visualization, infrastructure, and business teams.
• Organized, detail-oriented, with strong problem-solving skills and a solutions-first mindset.
• Proactive approach & Ability to prioritize and support multiple projects simultaneously

 

Qualifications

• Bachelor’s degree in computer science, Information Technology, Engineering, or a related field.
• 3+ years working experience in any data engineering and analytics related roles
• Proven experience in data engineering, data warehousing, ETL development, data migration, and Python-based automation.
• Hands-on experience developing and supporting production-grade data pipelines using SQL and Python.
• Experience working with large datasets and cloud-based data warehouse environments.
• Strong analytical, problem-solving, documentation, and stakeholder-management skills.

Technical skills (must-haves)

• Advanced SQL, including complex joins, CTEs, window functions, explain plans, and performance tuning.
• Strong Python experience for data processing, ETL development, automation, testing, and troubleshooting.
• Hands-on experience with AWS, Amazon Redshift and SQL-based ETL/ELT frameworks.
• Knowledge of data modelling, incremental loads, CDC, partitioning, and referential integrity.
• Familiarity with Git, CI/CD, Shell scripting, service accounts, and secrets management.

 

 

Required Skills:

 

 

Preferred Skills:

Analytical Reasoning, Analytics Insights, Big Data Management, Brand Positioning Strategy, Business Behavior, Business Data Analysis, Communication, Competitive Landscape Analysis, Customer Analytics, Customer Intelligence, Data Analysis, Data Savvy, Data Visualization, Execution Focus, Financial Analysis, Innovation, Marketing Insights, Market Research, Problem Solving