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Senior Data Engineer, Asset Management

Isgsearch — Canada · Posted ~23 hours ago

Senior Contract

Skills

Asset management domain expertise Snowflake Data engineering Cloud-native data platforms AWS Azure GCP Python Java Scala SQL Oracle Hadoop Data ingestion Data flow management ETL pipelines API design Microservices Cloud data architecture Query optimization Cost governance S3 EC2 EKS Glue SageMaker Athena Redshift APIs

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Summary ✨ AI‑Generated

Join a complex financial services organization as a Senior Data Engineer specializing in asset management. You will lead large-scale data initiatives, develop cloud-native platforms and pipelines, optimize enterprise data ecosystems, and design APIs and microservices. The role requires extensive asset management experience, strong Snowflake proficiency, and advanced programming skills across Python, Java, Scala, and SQL.

Highlights

A 12-month contract offering the opportunity to lead large-scale data initiatives in the financial services sector, work with modern cloud technologies, and design sophisticated data platforms and pipelines.

Description

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.