CBTS
CBTS serves enterprise and midmarket clients in all industries across the United States and Canada. CBTS combines deep technical expertise with a full suite of flexible technology solutions--including Application Modernization, Managed Hybrid Cloud, Cybersecurity, Unified Communications, and Infrastructure solutions. From developing and deploying modern applications and the secure, scalable platforms on which they run, to managing, monitoring, and optimizing their operations, CBTS delivers comprehensive technology solutions for its clients' transformative business initiatives. For more information, please visit www.cbts.com .
OnX is a leading technology solution provider that serves businesses, healthcare organizations, and government agencies across Canada. OnX combines deep technical expertise with a full suite of flexible technology solutions—including Generative AI, Application Modernization, Managed Hybrid Cloud, Cybersecurity, Unified Communications, and Infrastructure solutions. From developing and deploying modern applications and the secure, scalable platforms on which they run, to managing, monitoring, and optimizing their operations, OnX delivers comprehensive technology solutions for its clients’ transformative business initiatives. For more information, please visit
www.onx.com
.
Location:
[Insert Location] Experience:
6+ years Employment Type:
Full-time
Role Overview: We are looking for a highly skilled
Senior Data Engineer
with strong expertise in
Python
and
PySpark
to design, build, and optimize scalable data pipelines and platforms. The ideal candidate will work closely with data scientists, analysts, and business stakeholders to ensure efficient data processing and availability for analytics and machine learning initiatives.
Key Responsibilities:
Design, develop, and maintain
data pipelines
using Python and PySpark for large-scale data processing.
Implement
ETL workflows
for structured and unstructured data from multiple sources.
Optimize data storage and retrieval for
high-performance distributed systems
.
Collaborate with cross-functional teams to define
data architecture and governance standards
.
Ensure
data quality, integrity, and security
across all processes.
Monitor and troubleshoot data pipelines for
performance and reliability
.
Work on
cloud-based platforms
(AWS, Azure, or GCP) and big data ecosystems.
Mentor junior engineers and contribute to
best practices and code reviews
.
Required Skills & Qualifications:
Strong programming skills in
Python
and
PySpark
.
Hands-on experience with
big data frameworks
(Apache Spark, Hadoop).
Proficiency in
SQL
and working with relational and NoSQL databases.
Experience with
data modeling, partitioning, and optimization techniques
.
Familiarity with
cloud services
(AWS Glue, EMR, Databricks, or similar).
Knowledge of
CI/CD pipelines
and version control (Git).
Strong problem-solving and analytical skills.
Preferred Skills:
Experience with
streaming technologies
(Kafka, Spark Streaming).
Exposure to
containerization
(Docker, Kubernetes).
Understanding of
data governance and compliance
.
Education:
Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
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OnX is a leading technology solution provider that serves businesses, healthcare organizations, and government agencies across Canada. OnX combines deep technical expertise with a full suite of flexible technology solutions—including Generative AI, Application Modernization, Managed Hybrid Cloud, Cybersecurity, Unified Communications, and Infrastructure solutions. From developing and deploying modern applications and the secure, scalable platforms on which they run, to managing, monitoring, and optimizing their operations, OnX delivers comprehensive technology solutions for its clients’ transformative business initiatives. For more information, please visit
www.onx.com
.
Location:
[Insert Location] Experience:
6+ years Employment Type:
Full-time
Role Overview: We are looking for a highly skilled
Senior Data Engineer
with strong expertise in
Python
and
PySpark
to design, build, and optimize scalable data pipelines and platforms. The ideal candidate will work closely with data scientists, analysts, and business stakeholders to ensure efficient data processing and availability for analytics and machine learning initiatives.
Key Responsibilities:
Design, develop, and maintain
data pipelines
using Python and PySpark for large-scale data processing.
Implement
ETL workflows
for structured and unstructured data from multiple sources.
Optimize data storage and retrieval for
high-performance distributed systems
.
Collaborate with cross-functional teams to define
data architecture and governance standards
.
Ensure
data quality, integrity, and security
across all processes.
Monitor and troubleshoot data pipelines for
performance and reliability
.
Work on
cloud-based platforms
(AWS, Azure, or GCP) and big data ecosystems.
Mentor junior engineers and contribute to
best practices and code reviews
.
Required Skills & Qualifications:
Strong programming skills in
Python
and
PySpark
.
Hands-on experience with
big data frameworks
(Apache Spark, Hadoop).
Proficiency in
SQL
and working with relational and NoSQL databases.
Experience with
data modeling, partitioning, and optimization techniques
.
Familiarity with
cloud services
(AWS Glue, EMR, Databricks, or similar).
Knowledge of
CI/CD pipelines
and version control (Git).
Strong problem-solving and analytical skills.
Preferred Skills:
Experience with
streaming technologies
(Kafka, Spark Streaming).
Exposure to
containerization
(Docker, Kubernetes).
Understanding of
data governance and compliance
.
Education:
Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
#J-18808-Ljbffr