Contract Period: 18 Months

Working Location: Central / 2 days WFH

Role Overview

We are seeking a Full Stack / Data Engineer to design and build a high-performance data ingestion and API platform for data. The role will focus on cloud-based ingestion pipelines, time-series data storage, quality control logic, and APIs for high-frequency data insertion and retrieval.

The ideal candidate has strong experience building scalable backend systems for real-time or near-real-time data, with the ability to work across ingestion architecture, data modelling, API design, and operational reliability.

Key Responsibilities

• Architect and implement high-throughput data ingestion pipelines for telemetry and sensor data.
• Build backend services and APIs for data insertion, retrieval, configuration, and operational platform functions.
• Design low-latency RESTful, gRPC, or equivalent APIs for high-frequency time-series workloads.
• Implement streaming or near-real-time quality control logic, including anomaly detection and configurable validation rules.
• Design non-proprietary time-series schemas that support efficient storage, retrieval, governance, and future extensibility.
• Support access control, data governance, auditability, and secure integration patterns.
• Collaborate with IoT/network engineers to define ingestion contracts, payload formats, protocol boundaries, and error handling.
• Work with stakeholders to validate performance, stability, and reliability against agreed platform requirements.
• Contribute to system documentation, deployment notes, API specifications, and operational handover materials.

Required Skills and Experience

• Strong backend engineering experience with high-throughput, cloud-based data platforms.
• Experience designing and operating data ingestion pipelines for streaming, telemetry, sensor, IoT, or time-series data.
• Proficiency in at least one modern backend language such as Python, Java, Go, Node.js, or similar.
• Experience designing production-grade APIs, including REST, gRPC, or equivalent programmatic interfaces.
• Familiarity with time-series databases, relational databases, data lakes, or scalable storage systems.
• Understanding of performance tuning, data partitioning, batching, backpressure, observability, and reliability patterns.
• Ability to work across data engineering, backend development, and platform integration concerns.

Good to Have

• Experience with cloud services, containerized deployments, CI/CD, infrastructure-as-code, or managed streaming technologies.
• Familiarity with data quality frameworks, rules engines, or anomaly detection for operational data.
• Experience with environmental, geospatial, industrial IoT, or mission-critical data systems.

Pay: $7,000.00 - $8,500.00 per month

Work Location: In person