Job Overview

Adobe is hiring a Data Solutions Engineer in Bangalore to help build scalable data products, automation workflows, and AI-enabled solutions. The role is part of a Digital Transformation and Data Intelligence team and is designed for an experienced engineer who can turn unclear business challenges into reliable production solutions.

The position combines strong data engineering with practical product thinking. You will work across data pipelines, schemas, APIs, automation, cloud platforms, and AI-assisted engineering. The goal is to help business teams make better decisions, reduce repetitive work, improve data quality, and create measurable value from enterprise data.

This is an individual contributor role with opportunities to influence engineering standards, contribute reusable technical patterns, review solutions, and mentor other engineers. The successful candidate should be comfortable working across multiple systems and communicating with both technical and non-technical stakeholders.

Key Responsibilities

• Design, develop, and maintain scalable data solutions, including data pipelines, streams, schemas, interfaces, and workflow automation.
• Convert ambiguous business requirements into practical technical designs, implementation plans, and production-ready solutions.
• Build automation that improves data quality, reduces manual processes, and increases operational efficiency.
• Integrate and optimize information from internal and external data sources.
• Develop reliable data models and services that support business and operational needs.
• Apply modern software engineering practices across the complete development lifecycle.
• Use source control, automated testing, CI/CD, code reviews, documentation, monitoring, and production support processes.
• Create reusable engineering patterns that can be applied across data products and future initiatives.
• Participate in technical design discussions and help shape engineering standards.
• Work closely with business collaborators, analysts, program leaders, architects, and software engineers.
• Evaluate emerging tools and approaches that can improve data engineering and automation.
• Use AI-assisted development tools responsibly, validating generated outputs and maintaining engineering quality.
• Review code and designs and provide constructive guidance to other engineers.
• Mentor team members and support adoption of effective development practices.

Required Skills

Strong SQL and Python skills are central to this position. Candidates should have practical experience building dependable data pipelines, data models, APIs, and automated workflows.

A strong understanding of data engineering principles is required, including data quality, governance, security, access control, reliability, and production operations. Candidates should be able to work with data from different systems and design solutions that remain maintainable as workloads grow.

Experience with cloud data platforms, data warehouses, orchestration technologies, Git-based development, and CI/CD practices is important. The role also requires the ability to understand system dependencies and deliver solutions that work across multiple technical and business domains.

Candidates should be comfortable using LLMs or other AI-assisted development tools to improve engineering productivity. The expectation is not simply to use AI-generated output, but to review, validate, test, and refine it before it becomes part of a production solution.

Preferred Skills

Experience leading complex technical initiatives involving multiple systems, stakeholders, and business areas is highly relevant. Candidates who have worked on automation engineering, analytics engineering, software engineering, or modern data product development can bring useful breadth to the role.

Experience establishing reusable engineering standards, improving development processes, reviewing architecture or code, and mentoring engineers can also strengthen an application.

Strong product thinking is valuable because the position requires translating business needs into solutions that are practical, scalable, and useful to end users.

Education

A Bachelor’s degree or equivalent practical experience in Computer Science, Data Engineering, Information Systems, a related field, or equivalent practical experience is required.

Experience

The role requires 7+ years of experience in data engineering, analytics engineering, software engineering, automation engineering, or a related technical discipline. Candidates should demonstrate hands-on experience delivering production data solutions rather than only theoretical knowledge.

Experience working across multiple systems and business domains is particularly relevant. Applicants should be prepared to show how they have handled complex requirements, improved data processes, supported production systems, and delivered measurable engineering outcomes.

Required Technologies

Key technologies and technical areas include SQL, Python, data pipelines, data models, APIs, automation workflows, cloud data platforms, data warehouses, orchestration tools, Git, source control, CI/CD, automated testing, monitoring, data governance, security, access controls, LLMs, and AI-assisted development tools.

Candidates should also have practical experience with data quality and production reliability practices.

Soft Skills

The position requires strong communication and collaboration skills. Data Solutions Engineers must be able to explain technical decisions, limitations, and tradeoffs clearly to engineers as well as business stakeholders.

A structured problem-solving approach is important when requirements are incomplete or span multiple systems. The role also values ownership, curiosity, adaptability, and the ability to learn emerging technologies.

Mentoring and code review responsibilities require engineers to provide useful feedback while helping maintain consistent engineering standards across the team.

Benefits of Working in this Role

This role offers the opportunity to work at the intersection of data engineering, automation, software development, and AI-enabled solutions. Engineers can gain broader experience by working with business teams, analysts, architects, and engineering groups on practical enterprise data problems.

The position also provides exposure to modern engineering practices and opportunities to contribute reusable patterns, technical standards, automation, and AI-assisted development approaches.

Work Mode

The job description does not specify a remote or hybrid work arrangement. No work mode has been assumed beyond the information provided in the posting.

Location

Bangalore, Karnataka, India.

Who Should Apply

This opportunity is suitable for experienced data engineers and software engineers with 7+ years of relevant professional experience. Candidates should be confident with SQL and Python and have practical experience building reliable data pipelines, data models, APIs, and automated workflows.

Engineers who have worked with cloud data platforms, warehouses, orchestration tools, Git, CI/CD, monitoring, and enterprise data governance should highlight those capabilities on their resumes.

Applicants with experience using LLMs or AI-assisted development tools should describe how they have applied these technologies while maintaining code quality, testing standards, security, and reliability.

Career Growth

The role can help experienced engineers expand into senior data engineering, data platform engineering, automation architecture, AI-enabled engineering, technical leadership, and data product roles. Exposure to business problem-solving and cross-functional delivery can also strengthen product and architecture skills.

The opportunity to mentor engineers and influence reusable technical patterns can support progression toward broader technical leadership responsibilities.

Application Advice

Emphasize your 7+ years of relevant experience and provide clear examples of production data solutions you have delivered. Highlight strong SQL and Python skills, especially where you used them to build pipelines, models, APIs, or automation.

Include experience with cloud data platforms, data warehouses, orchestration, Git, CI/CD, testing, monitoring, security, governance, and production support. If you have led initiatives across several systems or business teams, explain your role and the outcome.

AI experience should be presented with practical examples. Mention LLM or AI-assisted development work where you validated outputs, improved engineering productivity, or built useful automation while maintaining quality standards.

Apply now through SoftoJobs to explore this opportunity.