Ghostless: tech jobs with the record job boards don't keep

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Open 8 days

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It hasn't been reposted, listed twice, or left up unusually long, and the posting doesn't say it's a talent pool.

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Last checked Nov 2, 2026.

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7–8 years of experience: “7 to 8 years of experience as a Data Engineer or in a similar role, with expertise in building and maintaining data pipelines and infrastructure.” (quoted from the posting)

Not stated: Pay, real vacancy, AI screening.

Why these three

Ontario requires postings from employers with 25 or more staff to state the pay, whether the vacancy exists, and whether AI screens applicants.

Some employers add pay only on their own site. Check the original posting before you rule it out.

Design, develop, and maintain scalable ETL/ELT pipelines to ingest, transform, and integrate data from various sources.
Implement real-time data streaming and batch processing solutions to support diverse business needs.
Build and optimize data storage solutions, including data lakes, data warehouses, and databases.
Ensure data systems and pipelines are scalable, secure, and performant.
Clean, transform, and prepare raw data into usable formats for analytics and machine learning.
Collaborate with Data Scientists and Analysts to define data requirements and deliver solutions.
Monitor the performance and reliability of data pipelines and systems, implementing improvements where necessary.
Troubleshoot and resolve data-related issues, ensuring minimal downtime.
Implement and enforce data quality checks, validation processes, and monitoring mechanisms.
Collaborate with Data Governance teams to ensure data complies with organizational standards and policies.
Work closely with cross-functional teams, including Data Architects, Analysts, and Business
Teams, to understand requirements and deliver data solutions.
Provide technical expertise and guidance on data engineering best practices.
Stay updated on emerging tools, technologies, and industry trends.
Evaluate and recommend technologies to enhance data engineering capabilities

Requirements

Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Systems, or a related field.

7 to 8 years of experience as a Data Engineer or in a similar role, with expertise in building and maintaining data pipelines and infrastructure.

Hands-on experience with big data tools, cloud platforms, and data integration techniques.

Expertise in SQL and working with relational and NoSQL databases.

Experience with data orchestration tools (e.g., ODI, SSIS, Apache Airflow, dbt, Prefect).

Proficiency in programming languages like Python, Java, or Scala.

Familiarity with data processing frameworks (e.g., Apache Spark, Kafka).

Strong problem-solving and analytical skills.

Excellent communication and collaboration abilities.

Ability to work in a fast-paced, team-oriented environment.

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