Job Summary

We are seeking a highly skilled Lead Software Engineer - Data Engineering for the development of Caterpillar's next-generation Digital Manufacturing Data Platform. This platform enables large-scale data ingestion, transformation, and analytics across manufacturing, supply chain, and engineering ecosystems. The ideal candidate will bring deep expertise in data engineering, large-scale data ingestion, AWS-based architectures, and Snowflake, along with robust leadership and software engineering discipline.

The preference for this role is to be based out of Chennai - Brigade World Trade Center

What You Will Do

Leadership Delivery

- Lead and mentor a team of data engineers and platform developers
- Drive Agile execution and ensure predictable, high-quality delivery
- Establish engineering best practices, code quality, and CI/CD standards

Data Platform Architecture

- Architect scalable and secure data platforms on AWS
- Design robust data ingestion frameworks for batch and near real-time pipelines
- Define best practices in data modeling, governance, and metadata management

Data Engineering Ingestion

- Lead design and development of scalable ingestion pipelines (structured and unstructured data)
- Build and optimize Snowflake-based data platforms for performance and cost
- Enable ingestion of diverse sources (databases, APIs, files, streaming data)

Cloud Platform Engineering

- Leverage AWS services (S3, Glue, Lambda, EMR, Redshift, etc.) for end-to-end pipelines
- Implement CI/CD pipelines using Azure DevOps / Jenkins
- Ensure system scalability, resiliency, and operational readiness

Software Engineering Excellence

- Enforce software engineering principles (modular design, code quality, testing, version control)
- Drive automation and continuous improvement
- Promote reusable frameworks for ingestion and transformation

Stakeholder Collaboration

- Partner with product managers, SMEs, and business stakeholders
- Translate business needs into scalable data solutions

What You Have

- 10+ years of experience in Data Engineering / Data Platform roles
- Strong experience in AWS data ecosystem (S3, Glue, Lambda, EMR, Redshift)
- Deep expertise in Snowflake (architecture, optimization, data modeling)
- Strong programming skills in Python and SQL




- Extensive experience with data ingestion pipelines and ETL/ELT frameworks
- Exposure to real-time streaming (Kafka, Spark Streaming)
- Experience with CI/CD tools (GitHub, Jenkins, AWS CloudFormation)
- Solid understanding of distributed systems and scalable architectures
- Strong foundation in software engineering principles (Git, testing, design patterns)
- Experienced in working with Agile teams
- Collaborate with Data Science and AI teams to operationalize ML models and analytics workflows.
- Promote integration of AI capabilities into data engineering pipelines (e.g., GenAI, MCP, ATA).
- Support real-time analytics and edge AI use cases in manufacturing environments.
- Use AI extensively in building and testing Data Ingestion and Data pipeline
- This position requires the candidate to work a 5-day-a-week schedule in the office

Nice-to-Have Skills

- Experience with Graph Databases (Neo4j, Neptune)
- Experience with Vector Databases (Milvus, OpenSearch)
- Knowledge of NVIDIA ecosystem and RAPIDS (cuDF, cuML, cuGraph)
- Experience integrating AI/ML pipelines or GenAI workflows

Qualifications

- Bachelor's or Master's degree in Computer Science / Engineering
- Proven track record in leading engineering teams and delivering at scale
- Strong leadership, communication, and stakeholder management skills

Skills Desired

Decision Making and Critical Thinking

- Decision Making and Critical Thinking: Knowledge of the decision-making process and associated tools and techniques; ability to accurately analyze situations and reach productive decisions based on informed judgment.
- Level Working Knowledge: Applies an assigned technique for critical thinking in a decision-making process.
- Identifies, obtains, and organizes relevant data and ideas.
- Participates in documenting data, ideas, players, stakeholders, and processes.
- Recognizes, clarifies, and prioritizes concerns.
- Assists in assessing risks, benefits and consideration of alternatives.





Effective Communications

- Effective Communications: Understanding of effective communication concepts, tools and techniques; ability to effectively transmit, receive, and accurately interpret ideas, information, and needs through the application of appropriate communication behaviors.
- Level Working Knowledge: Delivers helpful feedback that focuses on behaviors without offending the recipient.
- Listens to feedback without defensiveness and uses it for own communication effectiveness.
- Makes oral presentations and writes reports needed for own work.
- Avoids technical jargon when inappropriate.
- Looks for and considers non-verbal cues from individuals and groups.

Software Development

- Software Development: Knowledge of software development tools and activities; ability to produce software products or systems in line with product requirements.
- Level Extensive Experience: Conducts walkthroughs and monitors effectiveness and quality of the development activities.
- Elaborates on multiple-development toolkits for traditional and web-based software.
- Has participated in development of multiple or large software products.
- Contrasts advantages and drawbacks of different development languages and tools.
- Estimates and monitors development costs based on functional and technical requirements.
- Provides consulting on both selection and utilization of developers' workbench tools.

Software Development Life Cycle

- Software Development Life Cycle: Knowledge of software development life cycle; ability to use a structured methodology for delivering and managing new or enhanced software products to the marketplace.
- Level Working Knowledge: Describes similarities and differences of life cycle for new product development vs. new release.
- Identifies common issues, problems, and considerations for each phase of the life cycle.
- Works with a formal life cycle methodology.
- Explains phases, activities, dependencies, deliverables, and key decision points.

Disclaimer : This job posting & Location has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 LEAD SOFTWARE ENGINEER - DATA ENGINEERING (Chennai)
🏢 Caterpillar
📍 Chennai