M06 - Senior Software Engineer

About this role

Responsibilities

Design and develop scalable backend services integrating with external vendor systems via RESTful APIs

Implement robust data ingestion services including pagination and incremental/time-window retrieval

Handle API error handling, retries, and idempotent processing to ensure reliable integrations

Build and maintain data pipelines for processing large volumes of transactional and event data

Perform data transformation, validation, and enrichment for downstream systems

Support batch and near real-time data processing workflows

Develop and deploy applications using Microsoft Azure services such as Azure Functions, App Services, Storage, Key Vault, APIM, and VNET

Design scalable, resilient, and highly available cloud-native solutions

Implement observability practices including logging, monitoring, and alerting

Ensure data accuracy, consistency, and reconciliation across multiple data sources

Support auditability and traceability of data flows for regulatory requirements

Collaborate with external vendors on API contracts and integration designs

Deliver high-quality, maintainable, and reusable software solutions

Contribute to engineering standards, best practices, and continuous improvement initiatives

Support CI/CD pipelines, automated testing, and continuous delivery practices

Requirements
Core Technical Skills

Strong proficiency in Python (preferred) or backend languages such as Java or Node.js

Strong SQL proficiency including PostgreSQL, MySQL, or T-SQL

Solid experience building backend services and API integrations

Experience working with RESTful APIs and JSON payloads

Knowledge of secure integration patterns including API keys, TLS, certificates, and PGP

Good understanding of:

Pagination, filtering, and incremental data retrieval
Idempotency, retries, and distributed system failure handling

Experience with data visualisation tools such as Power BI, including connectivity and configuration

Data Engineering & Processing

Experience building batch or streaming data pipelines

Familiarity with data transformation, validation, and data modelling

Experience handling large datasets and high-volume ingestion systems

Understanding of data reconciliation and audit requirements is an advantage

Databases

Experience with relational databases such as PostgreSQL or MS SQL

Knowledge of query optimisation and large-scale data handling

Cloud & DevOps

Experience with cloud platforms, preferably Microsoft Azure

Experience setting up and managing CI/CD pipelines using GitLab CI/CD or similar tools

Familiarity with Docker/containerisation is an advantage

Observability & Reliability

Experience implementing logging, monitoring, metrics, and alerting solutions

Understanding of system reliability and fault-tolerant design principles

Originally posted on Himalayas