Toronto, On Genai platform engineer python Jobs – 88 Openings This Week

Big Data Developer - Vice President
Citi —Mississauga, ON
- $120,800–$170,800 a year
- Full-time
- Hybrid work
- Azure
- Master's degree
- SQL
Principal Applied AI Scientist (Team Lead), Digital and Global Investments
Royal Bank of Canada —Toronto, ON
- Full-time
- Azure
- Doctoral degree
- Computer Science
Senior Data Developer
Priceline.com —Toronto, ON
- Full-time
- Hybrid work
- Azure
- Computer Science
- DevOps
- Disability insurance
- Dental care
Sr Eng Mgr, Backend, Data & ML
eBay Inc. —Toronto, ON
- Full-time
- Computer Science
- Engineering
- System design
Managing Principal / Senior Director, Data Analytics Consulting
EPAM Systems, Inc. —Toronto, ON
- Azure
- SQL
- AWS
- Employee stock purchase plan
- Disability insurance
6d

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Big Data Developer - Vice President

Citi -
Mississauga, ON

Apply Now

Job details

Full-time
$120,800–$170,800 a year

Qualifications

Data modeling
Azure
Cloud architecture
HDFS
Big data
MapReduce
Spark
Encryption
UNIX
Google Cloud Platform
Apache Hive
Master's degree
Application development
SQL
AWS
Project management
Bachelor's
HBase
Linux
Leadership
Communication skills
Data warehouse
Python
High availability
Hadoop

Full job description

Discover your future at Citi

Working at Citi is far more than just a job. A career with us means joining a team of more than 230,000 dedicated people from around the globe. At Citi, you’ll have the opportunity to grow your career, give back to your community and make a real impact.

Job Overview

The Big Data Developer is a senior level position responsible for establishing and implementing scalable, efficient big data application systems and platforms—primarily across Hadoop/Spark and cloud environments—in coordination with the Technology team. The overall objective of this role is to lead big data systems analysis, data engineering, and applications programming activities.

Responsibilities:

Partner with multiple management teams to ensure appropriate integration of functions to meet goals, and to identify and define necessary platform and system enhancements to deploy new data products and process improvements.
Design and implement scalable and efficient Hadoop architecture solutions encompassing core ecosystem components, including HDFS, YARN, MapReduce, Hive, HBase, and Spark.
Collaborate with data engineers, data scientists, and analytics stakeholders to understand data requirements and deliver robust, reliable pipelines and analytical datasets.
Develop Spark/PySpark solutions to support near real-time data ingestion, analytics, and reporting, ensuring high performance and reliability.
Optimize Hadoop and Spark clusters for performance and resource utilization, including capacity planning, tuning, and job orchestration best practices.
Maintain and monitor Hadoop infrastructure to ensure high availability, reliability, and observability; implement proactive alerting, logging, and issue resolution.
Implement and enforce data security and governance policies (e.g., access controls, encryption, data quality, lineage, and cataloging) across big data platforms.
Troubleshoot and resolve issues across the Hadoop ecosystem (jobs, services, resource management), driving root-cause analysis and permanent fixes.
Provide expertise in the area and advanced knowledge of applications programming, ensuring application and data solution design adheres to the overall architecture blueprint and cloud reference patterns.
Utilize advanced knowledge of system flow to develop standards for coding, testing, debugging, deployment, and implementation—leveraging Python, PySpark, Unix/Linux, and SQL.
Develop comprehensive knowledge of how architecture, data platforms, and infrastructure integrate to accomplish business goals, including data modeling, ETL processes, data warehousing, and cloud-native services (AWS, Azure, Google Cloud).
Provide in-depth analysis with interpretive thinking to define issues and develop innovative, scalable solutions aligned with business and regulatory requirements.
Serve as advisor or coach to mid-level developers and analysts, allocating work as necessary and uplifting engineering practices through code reviews and mentorship.
Stay updated with the latest advancements in Hadoop/big data technologies and related areas; evaluate and introduce improvements, including AI/ML lifecycle management, MLOps, and GenAI-adjacent integrations where appropriate.
Appropriately assess risk when business decisions are made, demonstrating particular consideration for the firm’s reputation and safeguarding Citigroup, its clients and assets, by driving compliance with applicable laws, rules and regulations, adhering to Policy, applying sound ethical judgment regarding personal behavior, conduct and business practices, and escalating, managing and reporting control issues with transparency.

Recommended Qualifications:

6+ years of relevant experience in Big Data/Application Development or systems analysis roles, including building and operating production-grade data pipelines on Hadoop/Spark.
Extensive experience in system analysis and in programming of big data applications and data platforms.
Proven experience designing and managing Hadoop-based architectures, including cluster configuration, resource management (YARN), and ecosystem integration.
Strong understanding and hands-on expertise with the Hadoop ecosystem: HDFS, YARN, MapReduce, Hive, HBase, and Spark.
Strong hands-on and architectural knowledge of Python, PySpark, Unix/Linux, and SQL.
Experience with data modeling, ETL processes, and data warehousing concepts and implementation.
Experience implementing data security and governance (e.g., RBAC, encryption, data quality, data lineage, catalog).
Exposure to AI/ML lifecycle management, MLOps, and GenAI solution patterns and integration points.
Experience with major cloud platforms—AWS, Azure, Google Cloud—and related big data services (e.g., EMR, HDInsight, Dataproc, Databricks).
Subject Matter Expert (SME) in at least one area of Big Data/Application Development (e.g., Spark performance tuning, Hive optimization, HBase administration, data security).
Experience in managing and implementing successful projects; demonstrated leadership and project management skills.
Ability to adjust priorities quickly as circumstances dictate.
Consistently demonstrates clear and concise written and verbal communication.
Technical Proficiencies: Hadoop, HDFS, YARN, MapReduce, Hive, HBase, Spark; SQL; Data modeling; ETL; Data warehousing; AWS/Azure/Google Cloud.

Education:

Bachelor’s degree/University degree or equivalent experience
Master’s degree preferred

Job Family Group:

Technology

Job Family:

Applications Development

Time Type:

Full time

Primary Location Full Time Salary Range:

$120,800.00 - $170,800.00

Most Relevant Skills

Please see the requirements listed above.

Other Relevant Skills

For complementary skills, please see above and/or contact the recruiter.

Automated Processing and AI

We use automated processing, including artificial intelligence, for our legitimate business interests (or our reasonable and appropriate business purposes) to identify and align the candidate's skills and abilities with a specific job opening. Additionally, if you so choose, or consent, we can match your skills and abilities to other suitable roles at Citi.

Importantly, all our hiring processes and decisions, including determining your suitability for a role, are conducted, checked, and decided by individuals. Our automated processing and AI do not involve relying on automatic or autonomous decision-making. Please refer to any Jurisdictional Considerations, with specific provisions for your country (where relevant) for further details.

This job opening is for an existing job vacancy.

Citi is an equal opportunity employer, and qualified candidates will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other characteristic protected by law.

Apply Now

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genai platform engineer python jobs in toronto, on

Principal Applied AI Scientist (Team Lead), Digital and Global Investments

Senior Data Developer

Sr Eng Mgr, Backend, Data & ML

Managing Principal / Senior Director, Data Analytics Consulting

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Discover your future at Citi

Job Overview

Responsibilities:

Partner with multiple management teams to ensure appropriate integration of functions to meet goals, and to identify and define necessary platform and system enhancements to deploy new data products and process improvements.

Design and implement scalable and efficient Hadoop architecture solutions encompassing core ecosystem components, including HDFS, YARN, MapReduce, Hive, HBase, and Spark.

Collaborate with data engineers, data scientists, and analytics stakeholders to understand data requirements and deliver robust, reliable pipelines and analytical datasets.

Develop Spark/PySpark solutions to support near real-time data ingestion, analytics, and reporting, ensuring high performance and reliability.

Optimize Hadoop and Spark clusters for performance and resource utilization, including capacity planning, tuning, and job orchestration best practices.

Maintain and monitor Hadoop infrastructure to ensure high availability, reliability, and observability; implement proactive alerting, logging, and issue resolution.

Implement and enforce data security and governance policies (e.g., access controls, encryption, data quality, lineage, and cataloging) across big data platforms.

Troubleshoot and resolve issues across the Hadoop ecosystem (jobs, services, resource management), driving root-cause analysis and permanent fixes.

Provide expertise in the area and advanced knowledge of applications programming, ensuring application and data solution design adheres to the overall architecture blueprint and cloud reference patterns.

Utilize advanced knowledge of system flow to develop standards for coding, testing, debugging, deployment, and implementation—leveraging Python, PySpark, Unix/Linux, and SQL.

Develop comprehensive knowledge of how architecture, data platforms, and infrastructure integrate to accomplish business goals, including data modeling, ETL processes, data warehousing, and cloud-native services (AWS, Azure, Google Cloud).

Provide in-depth analysis with interpretive thinking to define issues and develop innovative, scalable solutions aligned with business and regulatory requirements.

Serve as advisor or coach to mid-level developers and analysts, allocating work as necessary and uplifting engineering practices through code reviews and mentorship.

Stay updated with the latest advancements in Hadoop/big data technologies and related areas; evaluate and introduce improvements, including AI/ML lifecycle management, MLOps, and GenAI-adjacent integrations where appropriate.

Recommended Qualifications:

6+ years of relevant experience in Big Data/Application Development or systems analysis roles, including building and operating production-grade data pipelines on Hadoop/Spark.

Extensive experience in system analysis and in programming of big data applications and data platforms.

Proven experience designing and managing Hadoop-based architectures, including cluster configuration, resource management (YARN), and ecosystem integration.

Strong understanding and hands-on expertise with the Hadoop ecosystem: HDFS, YARN, MapReduce, Hive, HBase, and Spark.

Strong hands-on and architectural knowledge of Python, PySpark, Unix/Linux, and SQL.

Experience with data modeling, ETL processes, and data warehousing concepts and implementation.

Experience implementing data security and governance (e.g., RBAC, encryption, data quality, data lineage, catalog).

Exposure to AI/ML lifecycle management, MLOps, and GenAI solution patterns and integration points.

Experience with major cloud platforms—AWS, Azure, Google Cloud—and related big data services (e.g., EMR, HDInsight, Dataproc, Databricks).

Subject Matter Expert (SME) in at least one area of Big Data/Application Development (e.g., Spark performance tuning, Hive optimization, HBase administration, data security).

Experience in managing and implementing successful projects; demonstrated leadership and project management skills.

Ability to adjust priorities quickly as circumstances dictate.

Consistently demonstrates clear and concise written and verbal communication.

Technical Proficiencies: Hadoop, HDFS, YARN, MapReduce, Hive, HBase, Spark; SQL; Data modeling; ETL; Data warehousing; AWS/Azure/Google Cloud.