Senior Big Data Engineer

Global Financial Firm located in MISSISSAUGA, ON has an immediate contract opportunity for an experienced Senior Big Data Engineer Pay Rate: $57.00 - $60.00 per hour Summary: Work Mode: Hybrid Location: Mississauga, ON Responsibilities: Build and maintain scalable data pipelines using PySpark within a Big Data environment to process and transform large volumes of structured and unstructured data. Design and develop solutions across the Hadoop ecosystem — including Hive, HDFS, Sqoop, Spark, Impala, and Scala — to enable efficient data ingestion, processing, and storage. Develop and manage real-time and batch data workflows using streaming data platforms, ensuring high availability and low-latency data delivery. Write complex SQL queries to extract, validate, and analyze data across distributed systems, supporting data-driven decision-making. Design and implement data models and data architecture patterns aligned with data warehouse principles, ensuring scalability, accuracy, and consistency. Automate pipeline scheduling and orchestration using shell scripting and Autosys, reducing manual intervention and improving operational reliability. Independently identify, assess, and resolve technical risks and data issues in a timely manner, maintaining system integrity across the data platform. Requirements: Minimum 6 years of professional developer experience. Hands-on expertise in PySpark and Big Data processing, with the ability to build and optimize distributed data workflows at scale. Practical knowledge of the Hadoop ecosystem, including Hive, HDFS, Sqoop, Spark, Impala, and Scala, applied in a production environment. Proficiency in complex SQL query development for data analysis, transformation, and validation across large datasets. Solid understanding of distributed systems architecture and how data flows across interconnected processing layers. Demonstrated knowledge of data modeling and data design, with familiarity in data warehouse concepts and dimensional modeling techniques. Competence in shell scripting and job scheduling using Autosys or equivalent workflow automation tools. Strong analytical and problem-solving ability, with a track record of working independently to diagnose and resolve complex data engineering challenges. Clear and effective communication skills, with the ability to articulate technical concepts to both technical and non-technical audiences. Preferred Skills: Experience in BI Platforms (preferably Tableau). Knowledge/experience with DataBricks. This role is for an existing vacancy.

Build and maintain scalable data pipelines using PySpark and the Hadoop ecosystem to process large volumes of structured and unstructured data. Develop real-time and batch workflows while automating pipeline scheduling using shell scripting and Autosys.

Requires a minimum of 6 years of professional developer experience with hands-on expertise in PySpark, Big Data processing, and complex SQL development. Candidates must have a strong understanding of distributed systems architecture and data modeling techniques.

• SQLSouhaitée
• TableauSouhaitée

Relevées dans la description du poste. Confirmez les exigences importantes ci-dessus.

• PySpark
• Hadoop
• Hive
• HDFS
• Sqoop
• Spark
• Impala
• Scala
• SQL
• Data Modeling
• Shell Scripting
• Autosys
• Data Warehousing
• Tableau
• DataBricks

• Data & Analytics
• Technology
• Software
• Engineering
• Finance & Accounting

Expérience minimale

5+ ans

Postuler avant le

9 sept. 2026

Langue de l’offre

anglais

Heures de travail

40 heures par semaine

Niveau d’expérience

Not Applicable

Mode de candidature

La candidature directe est offerte