Role: Data Engineer

Location: Toronto/ Vancouver (3 Days Hybrid)

Experience: 10+ Years

Duration-6+ Months Strong proficiency in Python, including Pandas, NumPy, PySpark, with hands on experience using Impala.

Proven experience working on Hadoop based platforms, performing large scale data extraction, transformation, and processing.

Robust SQL skills and experience working with both relational and distributed data stores.

Experience with enterprise data platforms and business intelligence ecosystems.

Hands on experience with ETL / ELT and data integration tools, such as Apache Airflow, Apache NiFi, Azure Data Factory.

Experience in data modelling, querying, data mining, and reporting over large volumes of granular data.

Exposure to machine learning concepts and analytical techniques used in advanced data solutions and Feature calculations and Model serving is a big plus.

8+ years of experience in data engineering, big data analytics, or enterprise data platforms, including 2+ years in a lead or technical leadership role.





Experience working with cloud based data platforms (Azure/AWS, Databricks/Snowflake), including data lakes, distributed compute, and storage services.

Experience implementing CI/CD pipelines and DevOps practices for data engineering workflows. GenAI / LLM Skills (Preferred)

Experience enabling GenAI/AI products through scalable, reliable data ingestion and transformation pipelines (batch and streaming).

Exposure to unstructured and semi-structured data processing (documents/logs/text) and building curated datasets for downstream consumption.

Strong understanding of data governance, privacy, and security requirements when using enterprise data with AI (PII handling, access control, auditability).

Familiarity with operationalizing AI data workflows (monitoring, data quality checks, reproducibility, and cost-aware scaling in cloud environments).

📌 Data Engineer (Toronto)
🏢 Spruce InfoTech
📍 Toronto