Senior Software Engineer - Backend

What You’ll Do:

• Setting up formal data practices for the company.
• Building and running super stable and scalable data architectures.
• Design, develop, and maintain scalable, high-throughput backend services and REST APIs using Java and Spring Boot.
• Designing and delivering solutions for low-latency data problems at scale.
• Making it easy for folks to add and use new data with self-service pipelines.
• Getting DataOps practices in place.
• Designing, developing, and running data pipelines to help out Products, Analytics, data scientists and machine learning engineers.
• Creating simple, reliable data storage, ingestion, and transformation solutions that are a breeze to deploy and manage.
• Writing and Managing reporting API for different products.
• Implementing different methodologies for different reporting needs.
• Develop event-driven and asynchronous services using messaging and streaming platforms such as Kafka, alongside other datastores.
• Follow and uphold engineering best practices around API design, code quality, testing, security, and data privacy, with healthcare compliance expectations in mind.
• Use AI across the SDLC - design, coding, testing, reviews, and documentation to deliver production-grade data solutions, owning the review, testing, and debugging of all AI-generated code.
• Teaming up with all sorts of people – business folks, other software engineers, machine learning engineers, and analysts.

Who You Are:

• Bachelor’s degree in engineering (CS / IT) or equivalent degree from a well-known Institute / University.
• 3.5+ years of experience managing data at scale and building and running both batch and streaming data pipelines.
• Experience with public clouds like GCP or AWS.
• Experience with Apache open-source projects like Spark, Kafka, Druid, Airflow, and big data databases like BigQuery, Clickhouse.
• Experience making data architectures that are optimised for both performance and cost.
• Solid grounding in microservices, REST API design, and distributed systems fundamentals; GraphQL or gRPC exposure is a plus.
• Experience with relational and NoSQL databases (e.g., PostgreSQL, MySQL, Aerospike, or similar), including schema design and query optimisation.
• Good grasp of software engineering, DataOps, data architecture, Agile, and DevOps.
• Proficient in SQL, Java, Spring Boot, Python, and Bash.
• Good communication skills for working with technical and non-technical people.
• Someone who takes ownership of problems and is solution-oriented — starts from the problem and the outcome, not just the ticket.
• AI-native delivery skillset — has shipped real work using AI across the SDLC (design, coding, testing, reviews, documentation), not just experimented with it.
• Hands-on with agentic coding tools (Claude Code, Cursor, Copilot, or similar), and quick to pick up new ones.
• Treats AI as a pair programmer, not a threat or a shortcut — and owns the output: can review, test, and debug AI-generated code, because “the AI wrote it” is never an excuse.
• Strong fundamentals in system design, data structures, and clean architecture.
• Understands security and data-privacy guardrails when using AI tools, particularly given the healthcare data we work with.
• Someone who thinks big, takes chances, innovates, dives deep, gets things done, hires and develops the best, and is always learning and curious.