Senior Data Engineer

1 week ago

Montreal, Quebec, Canada KData AI Full time $120,000 - $180,000 per year

About KData Inc.

At KData Inc., we don't just work with data – we unlock its potential. We are a forward-thinking data and AI solutions provider, empowering businesses to transform their operations through the power of the Lakehouse. Our team is a collective of passionate data professionals dedicated to building elegant, scalable, and impactful data platforms for our clients. Based in the vibrant heart of Montreal, we are immersed in a world-class tech ecosystem and are looking for a visionary engineer to help us shape the future of data.

The Role: Your Impact

As a Senior Databricks Engineer at KData, you will be the cornerstone of our technical delivery. You will architect, build, and optimize the core data platforms that solve our clients' most complex challenges. This is a hands-on, client-facing technical role where your expertise in the Databricks ecosystem will directly drive success and innovation. You will lead from the front, mentor colleagues, and leave your mark on every project you touch.

Key Responsibilities

  • Architect & Develop: Lead the design and implementation of large-scale, high-performance data processing systems on the Databricks Lakehouse Platform for our diverse client base.
  • Pipeline Excellence: Build robust, production-grade ETL/ELT pipelines using Spark, Delta Lake, and SQL to ingest and transform data from a multitude of sources.
  • Delta Lake Mastery: Architect and manage Delta Lake tables, implementing best practices for ACID transactions, schema enforcement/evolution, and time travel to build reliable data foundations.
  • Performance Tuning: Be the go-to expert for performance optimization. Profile, debug, and tune Spark jobs and cluster configurations for maximum efficiency and cost-effectiveness on Databricks.
  • Data Modeling & Governance: Design and implement scalable data models (e.g., Medallion Architecture). Champion data quality, reliability, and governance using tools like Unity Catalog.
  • CI/CD & Automation: Implement and advocate for modern DevOps practices in data engineering, using Databricks CLI/API, Git, Terraform, and CI/CD tools to automate deployment and testing.
  • Client Collaboration & Leadership: Work directly with client stakeholders to translate business needs into technical solutions. Provide technical guidance, mentor junior engineers, and lead technical presentations.
  • Cloud Infrastructure: Design and optimize cloud infrastructure on AWS, Azure, or GCP (please specify your primary cloud) integrated with Databricks, leveraging native services for security, storage, and compute.

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