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Senior Data Engineer

  • Canada

Full-time

This opening has closed.

The original listing is kept below for reference.

Job details

Job type
Full-time
Experience
5+ years of experience across data engineering, data architecture, or analytics solution design, with strong SQL and Python, PySpark, or Scala skills.
Posting language
English
Posted

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Original job description

Archived listing. The details below describe a past opening.

About the Company

This is a growing technology consulting firm focused on cloud, data, automation, and AI. The business works with clients on modernizing enterprise systems and solving complex data and technology challenges.

Its data practice delivers architecture and engineering work across major cloud platforms, with a strong focus on modern data platforms and Databricks-based environments.

The Role

This Senior Data Engineer will take ownership of designing and delivering scalable data platforms for client environments. The role combines hands-on engineering with architecture, technical leadership, and client-facing work, so it suits someone who can move comfortably between building pipelines, making design decisions, and explaining those decisions to stakeholders.

What You Will Do

  • Design modern data platforms spanning lakehouse, warehouse, ingestion, transformation, and analytics workloads.
  • Build and optimize batch and streaming pipelines using Databricks, Spark, Kafka, Delta Live Tables, and Autoloader.
  • Turn business and analytics requirements into practical data models, integration patterns, and technical architectures.
  • Lead data modernization and migration work, including moving traditional warehouse workloads onto Databricks-based platforms.
  • Improve platform reliability, performance, governance, and security while providing technical guidance to engineers and clients.

What You Bring

  • 5+ years of experience across data engineering, data architecture, or analytics solution design, with strong SQL and Python, PySpark, or Scala skills.
  • Hands-on experience with modern lake and warehouse technologies such as Databricks, Snowflake, Redshift, or Synapse, plus working knowledge of AWS or Azure.
  • Strong Databricks experience, including Autoloader, Delta Live Tables, Medallion architecture, and large-scale ETL/ELT pipeline development.
  • Experience building streaming ingestion with technologies such as Kafka and Spark Structured Streaming, alongside solid data modeling and integration fundamentals.
  • Experience implementing CI/CD for Databricks workloads using tools such as Azure DevOps, GitHub Actions, or GitLab CI, with the communication skills to present technical solutions directly to clients.

Why This Role

The scope goes well beyond maintaining pipelines. You will work across architecture, migrations, streaming, cloud infrastructure, governance, and client advisory work, with direct involvement in how modern data platforms are designed and delivered.

More about this job

Responsibilities

Design and deliver scalable data platforms, including lakehouse and warehouse architectures, for various client environments. Build and optimize batch and streaming pipelines while providing technical leadership and advisory services to stakeholders.

Requirements

Requires over 5 years of experience in data engineering or architecture with proficiency in SQL, Python, and Databricks. Candidates must have experience with streaming ingestion, CI/CD tools, and cloud platforms like AWS or Azure.

Skills

  • Databricks
  • Apache Spark
  • Python
  • SQL
  • PySpark
  • Scala
  • Kafka
  • Delta Live Tables
  • Azure DevOps
  • GitHub Actions
  • GitLab CI
  • Data Modeling
  • ETL/ELT
  • AWS
  • Azure
  • Snowflake

Visa sponsorship

Not detected in the job text

Categories

  • Data & Analytics
  • Technology
  • Consulting
  • Engineering
  • Software

Keywords

  • Databricks
  • Spark
  • Kafka
  • Delta Live Tables
  • Autoloader
  • Medallion Architecture
  • Lakehouse
  • Data Warehouse
  • PySpark
  • Scala
  • SQL
  • Python
  • AWS
  • Azure
  • Snowflake
  • Redshift
  • Synapse
  • CI/CD
  • Azure DevOps
  • GitHub Actions
  • GitLab CI
  • ETL
  • ELT
  • Data Modeling
  • Streaming Ingestion
  • Cloud Infrastructure
  • Data Governance
  • Data Modernization
  • IT Consulting
  • Data Engineering

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