We're looking for a Tech Lead who is more than a great data engineer – someone who brings equal depth in backend software engineering and broad fluency across data technologies, databases, and large-scale distributed systems. You'll own the architecture and hands-on development of our data platform while driving engineering excellence across the team.
Key Responsibilities
Architect and evolve our Data Warehouse, Data Lake, and ETL/ELT pipelines across multiple products and business domains
Design and build enterprise-grade backend services and APIs that expose data platform capabilities at scale
Own technical decisions on scalability, reliability, observability, and data quality
Lead cross-functional initiatives with R&D, product, analysts, and business stakeholders
Mentor data engineers and developers through design reviews, technical leadership, and engineering best practices
Drive adoption of modern data technologies, AI-first practices, and automation.
Key Responsibilities
Architect and evolve our Data Warehouse, Data Lake, and ETL/ELT pipelines across multiple products and business domains
Design and build enterprise-grade backend services and APIs that expose data platform capabilities at scale
Own technical decisions on scalability, reliability, observability, and data quality
Lead cross-functional initiatives with R&D, product, analysts, and business stakeholders
Mentor data engineers and developers through design reviews, technical leadership, and engineering best practices
Drive adoption of modern data technologies, AI-first practices, and automation.
Requirements:
6+ years in Data Engineering, including production-scale platform design and operation using Spark
2+ years as a Tech Lead or senior engineer leading technical initiatives
Hands-on backend development experience – REST/gRPC APIs, microservices, service design patterns – at enterprise scale
Broad database fluency: relational, analytical, NoSQL, columnar, and streaming stores
Advanced SQL and strong Python; proven experience building and optimizing large-scale ETL/ELT pipelines
Experience with cloud-based data platforms and AI-driven data workflows
Practical proficiency with AI agents and tools – building, integrating, or orchestrating LLM-powered workflows in production environments
Strong communication skills with technical and non-technical stakeholders
Self-directed and forward-thinking – you bring a clear point of view, drive initiatives without being told, and see around corners on where the platform needs to go next
Nice to have
Azure data services, Databricks or EventHub
Streaming and real-time data processing architectures
Background in cyber security, SaaS, or large-scale enterprise environments
Data governance, observability, or self-service platform experience.
6+ years in Data Engineering, including production-scale platform design and operation using Spark
2+ years as a Tech Lead or senior engineer leading technical initiatives
Hands-on backend development experience – REST/gRPC APIs, microservices, service design patterns – at enterprise scale
Broad database fluency: relational, analytical, NoSQL, columnar, and streaming stores
Advanced SQL and strong Python; proven experience building and optimizing large-scale ETL/ELT pipelines
Experience with cloud-based data platforms and AI-driven data workflows
Practical proficiency with AI agents and tools – building, integrating, or orchestrating LLM-powered workflows in production environments
Strong communication skills with technical and non-technical stakeholders
Self-directed and forward-thinking – you bring a clear point of view, drive initiatives without being told, and see around corners on where the platform needs to go next
Nice to have
Azure data services, Databricks or EventHub
Streaming and real-time data processing architectures
Background in cyber security, SaaS, or large-scale enterprise environments
Data governance, observability, or self-service platform experience.
This position is open to all candidates.
