Data Engineer – Enterprise AI & Data Platforms

Location: Bengaluru, India
Employment Type: Full-time

Build the Data Foundation for the Next Generation of Enterprise AI.

Great AI starts with great data. But in the enterprise, data is rarely clean, connected, or ready to use.

At ManoloAI, we're looking for a Data Engineer who enjoys solving complex data problems and wants to build the infrastructure that powers intelligent enterprise applications.

You'll work with data from ERP systems, procurement platforms, logistics networks, and other enterprise applications—turning fragmented information into reliable, scalable data foundations for analytics, AI agents, and automated decision-making.

This is an opportunity to build meaningful systems from the ground up, work alongside experienced engineers, and see your work directly influence how businesses operate.

About ManoloAI

ManoloAI is building the autonomous execution layer for enterprise supply chains.

Our mission is to help organizations transform data into intelligence, intelligence into decisions, and decisions into real-world outcomes.

Through our AI-native platform, Ariel, and our Forward Deployed Engineering teams, we help enterprises connect fragmented systems, make better decisions, and automate complex workflows across procurement, planning, and logistics.

We're a growing team of engineers, product thinkers, and supply chain technology veterans who believe enterprise AI should do more than generate insights. It should help businesses act on them.

And reliable, trusted data is the foundation that makes all of this possible.

The Opportunity

As a Data Engineer at ManoloAI, you'll help design and build the data platforms that power our AI-native products and enterprise customer solutions.

You'll work with real-world enterprise data that spans multiple systems, formats, and business processes. You'll build pipelines that ingest, transform, validate, and organize that data so it can be used confidently by analytics applications, AI agents, and operational workflows.

You'll collaborate closely with software engineers, AI engineers, product teams, and customer stakeholders to understand what the data represents, how it should be modeled, and how to make it reliable at scale.

Your work won't stop at moving data from one system to another. You'll help create the foundation for enterprise intelligence and autonomous execution.

What You'll Do

  • Build scalable data pipelines. Design, develop, and maintain reliable ingestion, transformation, and orchestration workflows.

  • Connect enterprise systems. Integrate data from ERP, procurement, inventory, logistics, finance, and other business applications using APIs, databases, files, and event-driven interfaces.

  • Design meaningful data models. Build standardized schemas, analytical data models, and reusable datasets that reflect real business processes.

  • Make data trustworthy. Implement data quality checks, validation, reconciliation, lineage, and monitoring.

  • Engineer for scale. Optimize pipelines and data processing workflows for performance, reliability, and growing data volumes.

  • Enable analytics and AI. Prepare trusted data for dashboards, forecasting models, conversational analytics, and AI-powered applications.

  • Automate operations. Build repeatable deployment, scheduling, testing, and monitoring processes for data infrastructure.

  • Collaborate across teams. Work with engineering, AI, product, and customer teams to translate business requirements into reliable data solutions.

  • Own the outcome. Troubleshoot production issues, improve system performance, and continuously strengthen data reliability.

What We're Looking For

We're looking for an engineer who enjoys working with data, understands the importance of good software engineering practices, and is curious about the business problems behind the data.

Ideally, you'll bring:

  • 2–5 years of experience in data engineering, backend engineering, or building production data platforms.

  • Strong proficiency in Python and SQL.

  • Experience designing and maintaining ETL/ELT pipelines.

  • Understanding of relational databases, data warehouses, and analytical data modeling.

  • Experience integrating data through APIs, database connectors, and file-based interfaces.

  • Familiarity with cloud platforms such as AWS, Azure, or Google Cloud.

  • Knowledge of data quality, pipeline orchestration, error handling, and monitoring.

  • Experience with Git, automated testing, and software development best practices.

  • Strong analytical thinking and problem-solving skills.

Experience in one or more of these areas is a plus:

  • Data orchestration tools such as Airflow, Dagster, or Prefect.

  • Modern data platforms such as Snowflake, Databricks, BigQuery, or Redshift.

  • Distributed processing frameworks such as Spark.

  • Streaming or event-driven data architectures.

  • Docker, Kubernetes, or infrastructure automation.

  • Enterprise data integration with SAP, Oracle, Infor, or other ERP systems.

  • Supply chain, procurement, inventory, or logistics data.

  • Preparing structured and unstructured data for AI agents, RAG, or machine learning applications.

You don't need experience with every tool on this list. We care more about your ability to reason through data problems, build reliable systems, and learn new technologies.

Who Thrives at ManoloAI

You'll feel at home here if you:

  • Are curious about where data comes from, what it means, and how it is used.

  • Enjoy untangling messy datasets and finding elegant solutions.

  • Take ownership of your work from design through production.

  • Believe data quality and reliability are as important as performance.

  • Think beyond the pipeline to understand the business outcome it supports.

  • Enjoy collaborating with engineers, data scientists, and business stakeholders.

  • Are comfortable working through ambiguity and making thoughtful engineering decisions.

  • Want to build systems that will grow with the company and its customers.

We value curiosity, ownership, customer empathy, humble swagger, and resourcefulness.

Why Join ManoloAI?

Build the foundation for enterprise AI. Your work will directly enable intelligent applications, AI agents, analytics, and automated business workflows.

Solve meaningful engineering problems. Work with complex enterprise data, multiple systems, and challenging integration requirements.

Own what you build. Contribute to architecture, implementation, deployment, and continuous improvement.

Work across technologies. Gain experience with cloud data platforms, enterprise integrations, AI applications, and modern data engineering practices.

Learn from experienced engineers. Collaborate with people who have built and scaled enterprise software and data systems.

Grow with the company. Help establish engineering practices, reusable components, and scalable data architectures as ManoloAI expands.

Ready to Build the Foundation for Intelligent Enterprises?

If you're an engineer who enjoys solving complex data challenges, takes pride in building reliable systems, and wants to see your work power real-world AI applications, we'd love to hear from you.

Please include your resume, LinkedIn profile, and, if available, examples of data engineering projects you've built.

Apply Now →