Senior Software Engineer, Data

Logward, a Shippeo company, is a pioneer in AI-powered supply chain execution workflows. As part of Shippeo — the global leader in real-time transportation visibility — Logward brings together trusted, SLA-backed visibility data with intelligent workflows and automation, helping global supply chain teams respond faster, reduce manual effort, and run more connected operations. *Please note: this role is locally employed by and contracted directly through Logward India Private Limited.* About the Role As a Senior Software Engineer, Data, you will contribute directly to Logward's core product mission by designing and building the data backbone that powers our No-Code Data Platform — enabling users worldwide to ingest, model, transform, validate, monitor, and operationalise data workflows without writing a single line of code. Working at the intersection of backend engineering and data systems, you will partner with product managers, architects, frontend engineers, and QA teams to ship scalable, enterprise-ready platform capabilities that drive real-world supply chain clarity. Location & Work Model: Location: Based in Bengaluru, India. Work Model: Hybrid (4 days per week in-office). Application Requirement: As we operate internationally, we kindly request all candidates to submit their CV in English. Applications submitted in other languages cannot be considered. Contract Type: Full-time Function: Engineering — Data Platform Key responsibilities Design & Build the Data Backbone: Architect and develop core platform capabilities for data ingestion, schema management, mapping, transformation, validation, orchestration, monitoring, and operational workflows — all in a no-code paradigm. Deliver Scalable Backend Services: Build robust APIs, background workers, and execution engines using Python, TypeScript, Go, or equivalent, following clean, well-tested, and production-ready engineering standards. Develop Configuration-Driven Frameworks: Create metadata-driven systems that allow users to define pipelines, business rules, and data mappings through configuration rather than code, enabling broad enterprise adoption without engineering dependencies. Enable High-Performance Data Processing: Leverage distributed processing frameworks (e.g. Apache Spark, Apache Flink) to build high-throughput ingestion and transformation capabilities supporting structured, semi-structured, and flat-file formats (JSON, XML, CSV, EDI, APIs). Build Platform Observability: Implement execution logs, audit trails, data lineage tracking, error handling, retry mechanisms, SLA monitoring, and data quality checks to ensure reliability at scale. Contribute to AI-Assisted Capabilities: Help shape and build AI-agent features including schema inference, mapping recommendations, anomaly detection, and pipeline troubleshooting — with robust tool orchestration, validation guardrails, and human-in-the-loop review. Champion Engineering Excellence: Conduct design reviews, mentor peers, uphold code quality standards, and contribute to a team culture centred on ownership, robustness, and continuous improvement. Proven backend engineering capability — experience building scalable APIs, workers, orchestration layers, or execution engines in Python, TypeScript, Go, or comparable languages, with strong object-oriented design and clean coding practices. Deep data engineering fundamentals — solid understanding of data ingestion, transformation, validation, orchestration, metadata management, and data quality monitoring. Database proficiency — hands-on experience with relational databases (PostgreSQL, MySQL) and NoSQL technologies (MongoDB, Redis, or similar). Data format & integration fluency — familiarity with structured, semi-structured, and flat-file formats (JSON, XML, CSV, EDI) and RESTful API integration, including async processing, message queues, and idempotency patterns. Workflow orchestration experience — practical use of tools such as Apache Airflow or equivalent platforms. Collaborative, product-oriented mindset — ability to translate complex product requirements into reusable, configurable platform features, while working effectively across engineering, product, and design functions. Preferred Qualifications (Nice-to-Haves) Experience with no-code/low-code platforms, ETL tooling, rule engines, workflow automation systems, data catalogs, or schema registries. Exposure to AI/LLM product development — including agents, function calling, RAG pipelines, structured outputs, evaluation frameworks, and enterprise guardrails. Understanding of modern data architectures — data warehouses, data lakes, lakehouses, and open table formats such as Apache Iceberg, Hudi, or Delta Lake. Familiarity with cloud-native development, Kubernetes, distributed workers, event-driven architectures, or object storage. Knowledge of data contracts, schema evolution, backward compatibility, data lineage, tenant isolation, and enterprise-grade security and auditability practices. A degree in Computer Science, Software Engineering, or a related technical discipline. Why Join Shippeo? At Shippeo, you will join a fast-moving company that values ambition, care, delivery, and collaboration. We offer an environment where impact is encouraged, ideas are valued, and development is supported. What sets us apart: Meaningful work with real-world impact in global supply chains. A diverse, inclusive, and international team. A culture of transparency, feedback, and continuous learning. Opportunities for growth, internal mobility, and professional development Hybrid work model and flexible policies. To learn more about our culture and people, visit our Careers section or explore team stories on our social platforms. Recruitment Process Preliminary call with a Talent Acquisition Manager Technical Round 1: Coding & Data Engineering Fundamentals Technical Round 2: Advanced Data Engineering & System Design Techno-Fitment round with the Hiring Manager Final interview Diversity and Inclusion At Shippeo, we are committed to fostering a diverse and inclusive workplace. We value the perspectives, experiences, and contributions of individuals from all backgrounds. Our policies, practices, and company culture reflect this commitment to equal opportunity and mutual respect. If you have specific needs or questions regarding disability inclusion, you may reach out to our dedicated Disability Advisor at [email protected] for support during the application process. This position is published via the Shippeo global talent platform on behalf of Logward, a Shippeo group company. The hiring entity and legal employer of record for this role is Logward India Private Limited. All interviews, offer letters, and employment contracts will be executed directly through Logward India.