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Data Engineering Lead

2 weeks ago

Toronto, Ontario, Canada Dew Software Full time $120,000 - $180,000 per year

Job Title: Data Engineering Lead

Location: Toronto, Ontario, Canada (Hybrid)

Experience Level: 8–10 Years

Employment Type: Contract - W2 Only

Position Overview

We are seeking a highly skilled and motivated
Data Engineering Lead
to design, build, and optimize scalable data pipelines and architectures for enterprise analytics and business intelligence platforms. The ideal candidate will have strong hands-on experience in
Python, PySpark, SQL, Snowflake
, and modern
ETL/Data Integration tools
, with a solid understanding of
data quality, governance, and performance optimization
.

This role requires both technical expertise and leadership ability to guide cross-functional teams in implementing robust data engineering solutions.

Key Responsibilities

  • Lead the end-to-end design and implementation of scalable data pipelines and ETL workflows for batch and real-time processing.
  • Develop, optimize, and maintain data models and data warehouse solutions on
    Snowflake
    or similar cloud data platforms.
  • Design and implement efficient
    PySpark
    and
    Python
    -based data transformations to handle large-scale structured and semi-structured data.
  • Collaborate with data analysts, data scientists, and business stakeholders to ensure high-quality, accessible, and trusted data.
  • Integrate data from multiple sources (on-prem, cloud, APIs) using
    ETL and data integration tools
    such as Informatica, Talend, Azure Data Factory, or similar.
  • Define and implement
    data quality checks
    , data validation frameworks, and exception handling mechanisms.
  • Manage and optimize data storage, partitioning, and query performance to meet SLAs.
  • Establish best practices for data engineering, version control, CI/CD for data pipelines, and monitoring solutions.
  • Provide technical leadership, code reviews, and mentorship to junior data engineers.
  • Ensure compliance with data governance, security, and privacy standards.

Required Skills and Qualifications

  • 8–10 years
    of experience in Data Engineering, with proven expertise in
    Python, PySpark, and SQL
    .
  • Strong experience with
    Snowflake
    (or equivalent data warehouse platforms such as Redshift, BigQuery, or Synapse).
  • Proficiency in
    ETL development
    and
    data integration tools
    (e.g., Informatica, Talend, DataStage, or Azure Data Factory).
  • Hands-on experience building
    data pipelines
    on cloud environments (AWS, Azure, or GCP).
  • Deep understanding of
    data quality frameworks, data validation, and data governance
    principles.
  • Solid experience with
    data modeling, performance tuning, and query optimization
    .
  • Experience implementing
    CI/CD
    and
    version control (Git, Jenkins)
    in data projects.
  • Excellent problem-solving, communication, and leadership skills.
  • Bachelor's or Master's degree in
    Computer Science, Information Systems, or related field
    .

Preferred Qualifications

  • Experience with
    orchestration tools
    such as Apache Airflow or Azure Data Factory.
  • Knowledge of
    data cataloging and lineage tools
    (e.g., Collibra, Alation).
  • Exposure to
    machine learning data pipelines
    or
    data lake architectures
    .
  • Familiarity with
    agile methodologies
    and
    DevOps for data
    practices.