Closed listing
Senior Data Engineer, Asset Management
- Toronto, ON, Canada
- Greater Toronto Area, Canada, Canada
Contract
This opening has closed.
The original listing is kept below for reference.
Job details
- Job type
- Contract
- Closing date
- Posting language
- English
- Posted
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Search current openingsOriginal job description
Archived listing. The details below describe a past opening.
Duration:
12 month contract
Must have:
7-8 years of experience in asset management is mandatory. Candidates must have hands-on experience working in the asset management domain and be highly proficient with Snowflake
1. 7+ years of experience working in data driven organizations on large scale, end to end data initiatives.
2. 5+ years of hands on experience building data platforms, applications, and pipelines using cloud native technologies (AWS, Azure, GCP).
3. Deep understanding of cloud data ecosystems (Snowflake - including Warehouses, query optimization, and cost governance, Oracle, Hadoop, etc.). Experience with data ingestion and flow management tools.
4. Strong programming skills in Python, Java, Scala, and SQL.
5. Expertise with AWS services including S3, EC2, EKS, Glue, SageMaker, Athena, and Redshift.
6. Experience designing APIs and microservices.
Our client…
A complex life insurance organization.
Responsibilities: * Design and implement end to end solutions for data, cloud, and software engineering needs.
* Collaborate with technical leads to align engineering decisions with the strategic vision of the client.
* Build scalable data pipelines, data lakes, and data warehouse solutions.
12 month contract
Must have:
7-8 years of experience in asset management is mandatory. Candidates must have hands-on experience working in the asset management domain and be highly proficient with Snowflake
1. 7+ years of experience working in data driven organizations on large scale, end to end data initiatives.
2. 5+ years of hands on experience building data platforms, applications, and pipelines using cloud native technologies (AWS, Azure, GCP).
3. Deep understanding of cloud data ecosystems (Snowflake - including Warehouses, query optimization, and cost governance, Oracle, Hadoop, etc.). Experience with data ingestion and flow management tools.
4. Strong programming skills in Python, Java, Scala, and SQL.
5. Expertise with AWS services including S3, EC2, EKS, Glue, SageMaker, Athena, and Redshift.
6. Experience designing APIs and microservices.
Our client…
A complex life insurance organization.
Responsibilities: * Design and implement end to end solutions for data, cloud, and software engineering needs.
* Collaborate with technical leads to align engineering decisions with the strategic vision of the client.
* Build scalable data pipelines, data lakes, and data warehouse solutions.
More about this job
Responsibilities
Design and implement end-to-end solutions for data, cloud, and software engineering, aligning technical decisions with the client’s strategic vision. Build scalable data pipelines, data lakes, and data warehouse solutions.
Requirements
Requires 7–8 years of hands-on asset management experience and strong proficiency with Snowflake, alongside 7+ years delivering large-scale data initiatives. Candidates should have 5+ years building cloud-native data platforms and pipelines, strong programming skills, AWS expertise, and experience with data ingestion, APIs, and microservices.
Skills
- Asset Management
- Snowflake
- Data Engineering
- Cloud Data Platforms
- Data Pipelines
- Data Lakes
- Data Warehousing
- Python
- Java
- Scala
- SQL
- AWS
- Data Ingestion
- Query Optimization
- API Design
- Microservices
Visa sponsorship
Not detected in the job text
Categories
- Data & Analytics
- Technology
- Software
- Finance & Accounting
Keywords
- Asset Management
- Snowflake
- Data Engineering
- Cloud-Native Technologies
- AWS
- Azure
- GCP
- Oracle
- Hadoop
- Data Ingestion
- Data Flow Management
- Python
- Java
- Scala
- SQL
- Amazon S3
- Amazon EC2
- Amazon EKS
- AWS Glue
- Amazon SageMaker
- Amazon Athena
- Amazon Redshift
- Data Platforms
- Data Applications
- Data Pipelines
- Data Lakes
- Data Warehouses
- API Design
- Microservices
- Query Optimization