Data Automation Specialist for Scalable Data Solutions

2 weeks ago

Toronto, Ontario, Canada MSI Corp Full time
About the Role

MSI Corp is seeking a skilled Data Automation Engineer to join our team. As a key member of our dynamic group, you will be responsible for designing and implementing automated data pipelines to support business analytics, reporting, and decision-making.

Key Responsibilities:
  • We are looking for a highly skilled professional to design, build, and maintain automated data pipelines that ingest, process, and transform data from various sources.
  • The successful candidate will improve the efficiency and scalability of data workflows by automating repetitive tasks such as data extraction, cleaning, and loading (ETL processes).
  • You will work closely with data scientists, analysts, and IT teams to ensure smooth data flow across the organization and correct data processing.
  • A key aspect of this role is developing automated validation checks and monitoring tools to ensure data quality and integrity throughout the pipeline.
  • We require someone to document automation processes, pipelines, and systems to ensure transparency and ease of understanding for stakeholders and future team members.
  • Continuous monitoring of the performance of automated data pipelines is essential, along with addressing any issues related to data quality, performance, or failures.
  • The ideal candidate will create automated solutions for generating and delivering reports, dashboards, or notifications to relevant stakeholders.
Requirements:
  • Bachelor's Degree in Computer Science, Data Engineering, Information Technology, or related field (or equivalent experience).
  • At least 3 years of experience in data automation, data engineering, or related roles.
  • Proficiency in Python or other scripting languages for data automation tasks.
  • Experience with ETL tools (e.g., Apache Airflow, Talend, Informatica, or custom Python-based pipelines).
  • Solid understanding of data storage technologies, such as relational databases (SQL), NoSQL, cloud storage, or data lakes.
  • Familiarity with cloud platforms (AWS, Google Cloud, Microsoft Azure) and related data services (e.g., S3, BigQuery, Redshift).
  • Experience with data processing frameworks like Apache Spark, Kafka, or Apache Beam is a plus.
  • Strong knowledge of data integration tools and techniques.
  • Ability to work with version control systems (e.g., Git) and CI/CD pipelines.
  • Understanding of data governance and best practices for data security and privacy.
Preferred Qualifications:
  • Experience with data visualization and reporting tools (e.g., Power BI, Tableau).
  • Familiarity with containerization (Docker, Kubernetes) for deployment of data automation tools.
  • Knowledge of machine learning workflows and automating data processes for ML model training and deployment is a plus.
Seniority level

Mid-Senior level

Employment type

Contract

Job function

Engineering and Information Technology

Industries

Telecommunications

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