Senior Data Engineer

ROLE
Firmus Technologies is seeking a Senior Data Engineer to join our Engineering and Technology team. You will drive the design and implementation of our data architecture. You will be accountable to achieve our mission to embrace data citizenship across the company as our competitive advantage. This role is ideal for a self-starter with passion for building things from first principles. You naturally break down complex problems into their fundamental truths to uncover novel and elegant solutions—rather than relying on conventional patterns.
KEY RESPONSIBILITIES
Implement high impact use cases to improve customer experience and operational efficiency (e.g. feed data for hardware failure prediction or Ops Copilot).
Define and maintain dimensional modelling standards and semantic layer strategy to support analytics, ML, and customer-facing use cases.
Architect and implement a scalable, company-wide and customer-facing data platform with standardized design patterns and a unified semantic layer.
Lead the implementation of data platform components including vector and columnar database, streaming processing, data lakehouse, data catalog and BI tools for the consumption of users or AI agents.
Collaborate with other teams and vendors on securely connecting multiple data sources e.g. telemetry, billings, and incidents.
Champion data citizenship within the company, support internal and external stakeholders through knowledge transfer and self-service tooling.
SKILLS AND EXPERIENCE
Bachelor's degree in computer science or a related technical field.
7+ years of experience in data engineering, ideally with a focus on cloud infrastructure operations and time series data.
Proven track record in designing and implementing large scale data platforms that integrate various components with data source from multiple regions
Strong proficiency in building, optimizing queries and partitioning large-scale datasets using columnar storage (e.g., Apache Parquet, ClickHouse, Delta Lake) for high-performance analytics.
Hands-on experience with modern orchestration, processing, and modelling tools (e.g., Airflow, dbt, Spark).
Solid understanding of embedding generation and integration with LLM-based workflows with vector database (e.g., Milvus) for semantic retrieval and AI agent context.
Working knowledge on data governance framework, semantic layer strategy, data security and data lineage automation.
Familiar with BI tools (e.g., Metabase, Tableau) to support a self-service analytics culture company wide.
Competent in SQL, scripting and programming skills.
Clear and effective communication in English, both written and spoken.
Bonus points: working experience in a high-growth startup company and/or highly regulated industry with robust security and data privacy requirements, including SOC 2 Type 2 and ISO 27001.