Data Engineer

Purpose:

This role is pivotal to build and maintain foundational data infrastructure that powers the company's AI, analytics, and operational systems.

Roles and Responsibilities:

• Data Architecture & Infrastructure
• Design and implement scalable, cloud-native data architecture that supports batch, streaming, and real-time processing needs.
• Define and enforce architectural standards, schemas, and data modeling best practices.
• Ensure compliance with data governance requirements to ensure the platform supports discoverability, lineage, and secure access.

Data Lake Development

• Design, build, and manage a centralized Azure Data Lake to support a unified data foundation across the business.
• Ingest and organize data from internal systems (e.g., ERP, historical data) and external sources (e.g., APIs, third-party providers, partner feeds).
• Structure the lake to support both raw and curated data, enabling diverse analytical and AI/ML use cases.
• Establish metadata management, cataloging, and versioning practices to ensure high usability and governance.

Data Pipeline Development

• Build and maintain robust, efficient ETL/ELT pipelines using modern orchestration and transformation tools (e.g., Data Factory, Synapse, Databricks, Apache Airflow).
• Integrate data from diverse sources, including internal systems, external APIs, third-party providers, and unstructured datasets to support advanced analytics and ML/GenAI use cases.
• Develop reusable, modular, and testable data components with version control, data quality checks, and observability baked in.

Data Quality, Security & Governance

• Implement monitoring, alerting, and logging systems to ensure data quality, integrity, and performance.
• Embed security-by-design principles including data classification, tagging, encryption, and access policies for sensitive data (e.g., PII, financial data).
• Align with Data Privacy and Data Security policies to implement tagging, classification, access controls, and policies for sensitive data (e.g., PII, financials).
• Contribute to compliance with relevant standards (e.g., GDPR, ISO27001) by aligning data processes with internal controls and audit requirements.

Innovation & Continuous Improvement

• Stay up to date with emerging data technologies, frameworks, and architectural paradigms (e.g., data lakehouse, data mesh).
• Identify and resolve platform bottlenecks, driving initiatives to enhance performance, reliability, and developer productivity.
• Participate in architectural reviews, proof-of-concepts (POCs), and long-term platform evolution aligned with the AI and analytics roadmap.

Qualifications/Skills:

• Experience with Azure Cloud Infrastructure
• Scalable data architecture expertise
• Startup and greenfield builder
• Code quality and accuracy focus
• Secure-by-design mindset

General:

• Ensure compliance with Nomia’s data protection and information security policies.
• Whilst this position is Hybrid, twice a week working from the office is required, possibly more whilst training and if requested by supervisor.
• Be aware at all times of diversity and inclusion and acting in line with Nomia’s core values.
• Foster and promote continuous improvement in systems and processes.

This role profile is not designed to be a comprehensive listing of all activities, responsibilities and tasks associated with the role, therefore these may change from time to time.