Big Data Lead
- Mississauga, ON, Canada
$120,000 to $125,000 CAD / year · Full-time
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Job details
- Pay
- $120,000 to $125,000 CAD / year
- Job type
- Full-time
- Apply by
- Experience
- 8+ years of experience in Big Data / Data Engineering.
- Posting language
- English
- Posted
Original job description
Job Title: Big Data Lead
Location: Mississauga, ON
Work Arrangement: Hybrid: 3 Days/Week WFO
Employment Type: Fulltime
Salary: CAD $120K-125K/Year
Domain: BFSI
Application Deadline: October 15th, 2026
About the Role
We are looking for an experienced Big Data Lead to design, develop, and maintain scalable data solutions using PySpark, Spark SQL, Python, and distributed computing technologies.
Job Description: -
Required Skills & Experience
- 8+ years of experience in Big Data / Data Engineering.
- Strong hands-on experience with PySpark and Apache Spark.
- Strong programming skills in Python.
- Excellent knowledge of Spark SQL and distributed data processing.
- Experience designing and developing ETL/ELT data pipelines.
- Strong understanding of distributed computing and big data concepts.
- Experience working with Hadoop/HDFS, Hive, cloud storage, or data lake platforms.
- Strong understanding of Spark performance tuning, including partitioning, caching, joins, shuffles, and resource optimization.
- Experience writing unit tests and data validation frameworks.
- Strong SQL skills and experience working with large datasets.
- Experience with data pipeline monitoring, troubleshooting, and production support.
EEOC Compliance:
We are an equal opportunity employer, and all qualified applicants will receive consideration for employment.
DISCLAIMER
AI Usage Policy: Pacer Group uses AI to assist in screening applications. Final hiring decisions are made by human recruiters based on qualifications and experience.
More about this job
Responsibilities
Design, develop, and maintain scalable big data solutions using PySpark, Spark SQL, Python, and distributed computing technologies. Build and support data pipelines, optimize Spark performance, and monitor and troubleshoot production data processes.
Requirements
Requires 8+ years of experience in big data or data engineering, with strong hands-on skills in PySpark, Apache Spark, Python, Spark SQL, and SQL. Candidates should have experience with ETL/ELT pipelines, distributed data processing, Hadoop/HDFS, Hive or cloud data platforms, Spark performance tuning, testing, data validation, and production support.
Skills
- PySpark
- Apache Spark
- Python
- Spark SQL
- Distributed Computing
- ETL/ELT Data Pipelines
- Hadoop/HDFS
- Hive
- Cloud Storage
- Data Lakes
- Spark Performance Tuning
- Unit Testing
- Data Validation
- SQL
- Data Pipeline Monitoring
- Production Support
Visa sponsorship
Not detected in the job text
Categories
- Data & Analytics
- Technology
- Software
- Management & Leadership
Keywords
- Big Data
- Data Engineering
- PySpark
- Apache Spark
- Python
- Spark SQL
- Distributed Computing
- Distributed Data Processing
- ETL/ELT
- Data Pipelines
- Hadoop
- HDFS
- Hive
- Cloud Storage
- Data Lakes
- Spark Performance Tuning
- Partitioning
- Caching
- Joins
- Shuffles
- Resource Optimization
- Unit Testing
- Data Validation Frameworks
- SQL
- Large Datasets
- Pipeline Monitoring
- Troubleshooting
- Production Support
- BFSI