Expert Software Engineer, Data Platform

Bangalore, India  

Development Manager 

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. 

We are looking for an Expert 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.  

• 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 

• 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 

• 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 

• 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 

• 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 

• Mentor engineers on distributed systems, Spark optimization, and API design 

• Promote best practices in data engineering, microservices, and software craftsmanship 

• Contribute to platform vision and long-term architectural evolution 

• 8+ years of software engineering experience with strong focus on data platforms and/or distributed systems 

• Hands-on expertise in Apache Spark or Scala or PySpark  

• Strong programming skills in Java (preferred) / Scala / Python 

• Experience building large-scale data pipelines (ETL/ELT) 

• Experience developing backend services or APIs (REST/microservices) 

• Deep understanding of: 

• Distributed systems (partitioning, shuffle, fault tolerance) 

• Data storage formats (Parquet, ORC, Avro) 

• Data modeling and schema evolution 

• Experience with cloud platforms (Azure/AWS/GCP) 

• Familiarity with workflow orchestration tools (Airflow, Dagster, etc.) 

• Strong system design and performance optimization skills 

• Experience with Spark Structured Streaming 

• Exposure to Lakehouse architectures (Delta Lake, Iceberg, Hudi) 

• Experience with event-driven architectures (Kafka, Event Hubs) 

• Knowledge of data governance, catalog, and lineage tools 

• Experience with CI/CD for data and microservices 

• Familiarity with Kubernetes and containerized workloads 

• Experience designing low-latency data serving APIs 

A successful engineer in this role will: 

• Deliver high-quality, production-grade data pipelines and APIs that power real business outcomes 

• Build systems that are scalable, observable, and resilient underload 

• Take ownership end-to-end, ensuring data flows reliably from source to consumer 

• Balance data correctness, performance, and cost efficiency 

• Contribute to evolving a modern data platform integrated with product-facing services 

You will work on foundational platform problems at scale, where data correctness, performance, and availability directly impact financial and healthcare outcomes. This role offers the opportunity to shape both data infrastructure and the APIs that bring it to life, in a system undergoing significant modernization. 

SHARED AMBITION. INSPIRED FUTURE. 

At Alegeus, our success is guided by our aligned vision and values—it is how we work together and collaborate to achieve our goals.  

• People First. We pride ourselves in bringing talented people together and treating one another with care.  

• Partner Powered. We are committed to empowering our partners, knowing our success is shared and we win as one.  

• Always Advancing. We are driven by potential and relentlessly determined to achieve our goals. 

“I truly believe that people who are well-skilled and talented can go wherever they want in this company. We want to create the best place anyone has ever worked.” - Alegeus employee