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Open nowFirst seen 6 days ago

ETL Data Engineer (Hybrid, Markham, Ontario)

HR POD - Hiring Talent Globally47 open roles

Where
Markham, ON, Canada
Work mode
Hybrid
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Your applicationOpen nowETL Data Engineer (Hybrid, Markham, Ontario)HR POD - Hiring Talent Globally · Markham, ON, Canada

  1. YouYes, apply to this one.

  2. CV RocketCV written for this posting.

  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

  4. CV RocketApplied on HR POD - Hiring Talent Globally's own form.

The reply lands in your private mailbox

3×more interviews than doing it yourself with ChatGPT.

The clock on this job

Early applications get read.

12.3% of postings close within 7 days. Measured by our own scanner across the market. HR POD - Hiring Talent Globally postings stay open a median of 1 days.

Share of postings closed within
  1. 2.1%1 day
  2. 4.5%3 days
  3. 12.3%7 days
  4. 19.7%14 days
  5. 35.6%30 days
  6. 58.0%60 days
This job: first seen 6 days ago

HR POD - Hiring Talent Globally median: 1 days open

The posting

Requirements:

  • 8+ years of hands-on experience in ETL development, Data Engineering, or enterprise data integration.
  • Strong expertise in Informatica, with proven experience developing and maintaining ETL workflows and data pipelines.
  • Hands-on experience working with Hadoop and large-scale data processing environments.
  • Advanced SQL skills, with strong experience working with complex datasets and queries.
  • Strong experience in data reconciliation, data validation, and data quality technologies.
  • Experience working with Business Intelligence tools and supporting reporting and analytics requirements.
  • Strong understanding of ETL architecture, data mapping, transformation, and data integration processes.
  • Experience in the insurance domain is preferred, while knowledge of P&C Insurance is a strong plus.

Responsibilities:

  • Design, develop, and maintain scalable ETL pipelines and data integration solutions using Informatica.
  • Develop data transformation and processing workflows across Hadoop and enterprise data environments.
  • Write and optimize advanced SQL queries for data extraction, transformation, reconciliation, and analysis.
  • Perform data reconciliation and validation to ensure data completeness, consistency, and accuracy across systems.
  • Identify and resolve data quality, integration, and ETL performance issues.
  • Support data requirements for Business Intelligence, reporting, and analytics platforms.
  • Collaborate with business, data, and technical teams to translate requirements into reliable and scalable data solutions.
  • Maintain comprehensive ETL documentation and ensure data pipelines adhere to established development, quality, and governance standards.
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