Expert Software Engineer, Data Platform

Do you want to shape the future of fintech and healthtech ? Energized by challenges and inspired by bold goals? Ready to elevate your career alongside driven and talented colleagues? If that sounds like you, explore a career at Alegeus today. Opportunity Happens Here . Senior Software Engineer – Data Platform   Location   Bangalore, India    Reports to   Development Manager   About Alegeus   Alegeus is the market leader in consumer-directed healthcare (CDH) solutions, powering millions of consumer benefit accounts including FSAs, HSAs, HRAs, dependent care and wellness programs through a modern SaaS and payments platform.

We are investing aggressively in modernization, API-first integration, real-time data access, and AI-enabled automation to redefine how consumers save and spend on healthcare. At this inflection point, we are transforming our platform, elevating engineering rigor, and building a next-generation product and engineering organization. Role summary   We are looking for a Senior Software Engineer to design, build, and scale our next-generation Data Platform and Data-Driven APIs.

This role combines distributed data processing (Apache Spark) with platform and microservices engineering (Java) to enable reliable, scalable, and real-time data access. You will operate at the intersection of data engineering and backend platform engineering - building systems that not only process large volumes of data but also expose that data through robust, well-designed APIs and services. This role goes beyond implementing requirements.

We expect engineers to understand business context, challenge assumptions, and take end-to-end ownership of delivering meaningful outcomes. Key responsibilities   Data Platform Engineering   Design and develop scalable data pipelines using Apache Spark (batch and streaming)   Build and maintain data platform layers: ingestion, transformation, and serving   Optimize Spark jobs for performance, cost, and reliability (partitioning, skew handling, memory tuning)   Implement data quality, observability, and lineage frameworks   Contribute to data architecture decisions ( Lakehouse , data mesh, storage formats, partition strategies)   Define and enforce data contracts and schema evolution practices   Platform APIs & Backend Engineering   Design and build data-driven platform APIs using Java (preferred )   Develop microservices that expose curated datasets for product and partner consumption   Implement RESTful APIs and event-driven services for real-time and near real-time data access   Ensure low-latency, high-availability data serving layers   Integrate with upstream/downstream systems, including legacy APIs where required     Cloud & Platform Integration   Build and deploy solutions on Azure (preferred) / AWS / GCP   Leverage cloud-native services for data storage, compute, and messaging   Work with event streaming systems (Kafka/Event Hubs) for real-time pipelines   Support containerized deployments and orchestration (Kubernetes) where applicable     Quality, Observability & Engineering Excellence   Champion   unit tests   across both data and service layers   Build automated validation frameworks for data pipelines   Implement end-to-end observability (metrics, logging, tracing) across pipelines and APIs   Drive CI/CD practices for both data and application code   Conduct code reviews and enforce engineering best practices     Product Mindset & Ownership   Engage deeply with product and business stakeholders to understand why, not just what   Translate business problems into scalable data and platform solutions   Take end-to-end ownership from design through production and support   Proactively identify performance bottlenecks, data issues, and system gaps     Mentorship & Leadership   Mentor engineers on distributed systems, Spark optimization, and API design   Promote best practices in data engineering, microservices, and software craftsmanship   Contribute to p