Senior Data Platform Engineer

Avaloq AG; Bosco Luganese; On-site; CHF 140,000 - 190,000; Full time

Job summary

Avaloq AG is seeking a Senior Data Platform Engineer to design, build, and operate a scalable data platform for security, audit, and analytics workloads. The role emphasizes data engineering, architecture, ingestion, and governance across batch and streaming pipelines.

You will collaborate with security, infrastructure, and analytics teams to deliver trusted data, improve accessibility, and support monitoring, compliance, and business insights.

Qualifications

• Experience designing and operating scalable data platforms.
• Proficient in building batch and streaming data pipelines.
• Knowledge of data governance, quality controls, and regulatory requirements.

Responsibilities

• Design and evolve scalable data platform architectures for security, audit, operational, and analytics data.
• Design, build, and maintain batch and streaming data pipelines with robust ingestion frameworks.
• Design relational, analytical, and event-based data models and optimize storage and performance.
• Define data quality controls and governance including lineage, metadata and retention policies.
• Integrate data from diverse platforms and enable analytics, SIEM, and reporting use cases.
• Develop data engineering tooling and automation with Python and Terraform, contributing to CI/CD.

Skills

Data platform engineering

Data modeling

Team collaboration

Tools

Python

SQL

Terraform

CI/CD

Job description

We are seeking a Senior Data Platform Engineer to design, build, and operate a scalable, secure, and governed data platform supporting security, audit, operational, and analytics workloads.

This role is primarily focused on data engineering and data platform development, including data architecture, ingestion pipelines, data modeling, quality controls, governance, and integration with analytics and security platforms. The successful candidate will have strong experience designing and operating data platforms, building reliable batch and streaming pipelines, and managing large volumes of structured and semi-structured data.

The role requires close collaboration with security, infrastructure, and application teams to deliver trusted, high-quality data that enables monitoring, reporting, threat detection, compliance, and business insights.

Your key tasks

Data Platform Architecture

• Design and evolve scalable data platform architectures for security, audit, operational, and analytics data
• Define data storage strategies, schemas, data models, partitioning, retention, and lifecycle management approaches
• Evaluate and prototype new technologies and architectures to improve scalability, performance, and cost efficiency

Data Engineering & Pipelines

• Design, build, and maintain batch and streaming data pipelines
• Develop robust ingestion frameworks for logs, audit data, application events, security telemetry, and operational datasets
• Implement data transformation, enrichment, normalization, correlation, and aggregation processes
• Ensure pipelines are reliable, scalable, observable, and resilient

Data Modeling & Storage

• Design relational, analytical, and event-based data models
• Optimize database structures, query performance, indexing, and storage efficiency
• Support the implementation of data lake, warehouse, and lakehouse concepts where appropriate

Data Quality & Governance

• Define and implement data quality controls across ingestion and transformation layers
• Develop validation, reconciliation, deduplication, and completeness checks
• Support data lineage, metadata management, ownership, retention, auditability, and regulatory requirements
• Implement controls for sensitive and regulated data

Platform Integration & Analytics Enablement

• Integrate data from diverse internal and external platforms, applications, databases, APIs, and messaging systems
• Deliver curated datasets that support reporting, analytics, observability, compliance, and security operations
• Support integration with SIEM, monitoring, and business intelligence platforms
• Collaborate with analytics and reporting teams to improve data accessibility and usability

Engineering & Automation

• Develop data engineering services, tooling, and automation using Python and SQL
• Contribute to CI/CD practices for data platform components
• Support infrastructure automation where required, using Terraform and related tooling
• Maintain engineering standards, documentation, and operational procedures