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- Experience level
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- Posting language
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Job summary
Develop and support large-scale data pipelines using Big Data technologies and distributed computing frameworks. Analyze data and business requirements, validate data quality, and optimize solutions for performance.
Job details
Job Title: Sr. Big Data Engineer Location: Mississauga, ON (On-site) Hire Type: Fulltime Job Description: Mandatory Skills: Big Data, 10-12 Years over all experience Required Skills: Strong hands-on experience in Python and PySpark. Expert-level proficiency in SQL for data analysis, reporting, and optimization. Strong experience with Big Data technologies and distributed computing frameworks. Hands-on development experience in Scala. Experience in data analysis, data profiling, and data quality validation. Strong understanding of ETL/ELT processes and large-scale data pipelines. Experience working with Spark, Hive, Hadoop, and related Big Data ecosystems. Ability to analyze complex business requirements and translate them into technical solutions. Strong debugging, performance tuning, and problem-solving skills.
What you’ll do
Develop and support large-scale data pipelines using Big Data technologies and distributed computing frameworks. Analyze data and business requirements, validate data quality, and optimize solutions for performance.
Requirements
Requires 10–12 years of overall experience, strong hands-on Python and PySpark skills, expert SQL proficiency, and hands-on Scala development experience. Candidates should also have experience with Spark, Hive, Hadoop, ETL/ELT processes, data profiling and validation, debugging, and performance tuning.
Listed skills
- Python · Preferred
- SQL · Preferred
- Data analysis · Preferred
Other relevant skills
Identified from the job description. Confirm important requirements above.
- Python
- PySpark
- SQL
- Big Data
- Distributed Computing
- Scala
- Data Analysis
- Data Profiling
- Data Quality Validation
- ETL/ELT
- Data Pipelines
- Spark
- Hive
- Hadoop
- Debugging
- Performance Tuning
Job areas
- Data & Analytics
- Technology
- Software
- Engineering
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