Job Overview

Adobe is hiring a Senior Data Engineer in Bangalore for a role focused on building scalable data pipelines, cloud data solutions, analytics platforms, and AI/ML-enabled capabilities. The position combines strong data engineering fundamentals with modern cloud technologies and business intelligence practices.

The role is suited to an experienced data professional who can work across ETL and ELT development, SQL and PL/SQL programming, cloud data platforms, reporting, automation, and emerging AI-enabled data solutions. You will help design and improve reliable data workflows that support analytics and business decision-making.

This opportunity is particularly relevant for professionals who have worked with enterprise data environments and want to expand their experience across Microsoft Azure, Databricks, Python, modern data stacks, and AI/ML applications.

Key Responsibilities

• Design, develop, maintain, and optimize enterprise data pipelines using ETL and ELT approaches.
• Build data integration workflows using SAP BODS and SnapLogic.
• Develop complex SQL and PL/SQL queries, stored procedures, functions, and packages for data extraction, transformation, processing, and reporting.
• Improve query performance and data-processing efficiency through appropriate optimization techniques.
• Design and implement scalable data solutions using Microsoft Azure and Azure data services.
• Work with Azure Databricks to support data engineering and analytics workloads.
• Develop Python-based solutions for data processing, automation, scripting, and pipeline orchestration.
• Create and maintain reporting and dashboard solutions using business intelligence tools.
• Collaborate on data solutions that support analytics requirements and business use cases.
• Contribute to AI/ML-enabled tools and integrate intelligent capabilities into data products where appropriate.
• Help maintain reliable data workflows across enterprise database and cloud environments.
• Apply sound engineering practices to improve the maintainability, scalability, and quality of data solutions.

Required Skills

Candidates should have strong practical experience in data engineering and data analytics, with at least 10 years of professional experience in relevant areas.

Hands-on experience with SAP BODS and SnapLogic is important for this position. Strong SQL and PL/SQL expertise is also required, including the ability to work with complex queries, stored procedures, functions, packages, and query optimization.

The role requires experience with enterprise databases, particularly Microsoft SQL Server and SAP HANA Analytics. Candidates should understand data extraction, transformation, storage, and reporting across on-premises environments.

Strong knowledge of Microsoft Azure and Databricks is expected. Python proficiency is also required for scripting, automation, data processing, and pipeline orchestration.

Experience with reporting and business intelligence tools such as Power BI or Tableau is valuable for building analytics solutions that communicate data effectively.

Preferred Skills

Experience with Delta Lake, Apache Spark, and modern data stack technologies is preferred. Familiarity with Large Language Models, machine learning pipelines, and AI/ML-enabled data products can further strengthen a candidate's profile.

Relevant technical certifications are also considered beneficial, although the job description does not identify a specific mandatory certification.

Education

A Bachelor's degree or equivalent experience in Computer Science, Engineering, Information Systems, or a related technical discipline is required.

Experience

The role requires 10 or more years of experience in data analytics or data engineering. Candidates should demonstrate substantial hands-on experience in enterprise ETL, SQL and PL/SQL development, databases, cloud data platforms, Python, reporting, and data pipeline engineering.

Senior-level applicants should be comfortable taking ownership of complex data solutions, optimizing existing workflows, and working across different technologies and data environments.

Required Technologies

• SAP BODS
• SnapLogic
• SQL
• PL/SQL
• Microsoft SQL Server
• SAP HANA Analytics
• Microsoft Azure
• Azure Databricks
• Python
• Power BI
• Tableau
• ETL
• ELT
• Data Pipelines
• Data Engineering
• Business Intelligence
• AI/ML
• Delta Lake
• Apache Spark
• Machine Learning Pipelines
• LLMs

Soft Skills

Strong analytical thinking is important for understanding complex data requirements, diagnosing pipeline issues, and optimizing data-processing workflows.

Senior data engineers should also be comfortable communicating technical concepts to engineering, analytics, and business stakeholders. Attention to detail is essential when working with enterprise data, SQL transformations, reporting, and data quality.

A proactive approach to problem solving, willingness to learn emerging technologies, and the ability to manage complex technical responsibilities will support success in this role.

Benefits of Working in this Role

This role provides an opportunity to work on large-scale data engineering and analytics challenges while combining established enterprise technologies with modern cloud and AI capabilities.

Professionals can deepen their expertise across Microsoft Azure, Databricks, ETL platforms, SQL, Python, business intelligence, and AI/ML-enabled data solutions. Experience with modern data stack technologies can also help broaden skills beyond traditional enterprise data engineering.

Work Mode

The provided job description does not specify a work-from-home, hybrid, or onsite arrangement. Candidates should confirm the current work model with Adobe during the application process.

Location

The position is based in Bangalore, Karnataka, India.

Who Should Apply

This role is suitable for Senior Data Engineers, Data Engineering Specialists, ETL Developers, Cloud Data Engineers, Data Analytics Engineers, and experienced data professionals with 10 or more years of relevant experience.

Candidates with strong SAP BODS, SnapLogic, SQL, PL/SQL, Microsoft SQL Server, SAP HANA, Azure, Databricks, and Python experience are particularly aligned with the requirements.

Professionals who also have experience with Power BI, Tableau, Spark, Delta Lake, machine learning pipelines, LLMs, or AI-enabled data products can bring additional value.

Career Growth

The role offers an opportunity to expand from traditional enterprise data engineering into cloud-native analytics and AI-enabled data platforms. Experience with Azure, Databricks, Python, modern data stack technologies, and machine learning workflows can support progression toward Data Engineering Lead, Cloud Data Architect, Data Platform Architect, Analytics Engineering Lead, or AI Data Engineering roles.

Application Advice

Highlight your strongest data engineering projects and clearly show your years of experience with ETL, SQL, PL/SQL, and enterprise databases. Mention hands-on work with SAP BODS and SnapLogic prominently because these are specifically identified in the requirements.

Showcase experience designing or optimizing data pipelines on Microsoft Azure and Databricks. Include examples of Python automation, query optimization, reporting solutions, and business intelligence work.

If you have worked with Delta Lake, Spark, modern data stack tools, LLMs, machine learning pipelines, or AI/ML-enabled analytics products, include those technologies in your resume. Use project examples to demonstrate improvements in scalability, processing performance, automation, reliability, or analytics capabilities.