Data Engineer- AML and Payment domain

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profile Job Location:

Toronto - Canada

profile Monthly Salary: Not Disclosed
profile Experience Required: 5years
Posted on: 2 hours ago
Vacancies: 1 Vacancy

Job Summary

Job Title: Data Engineer

Location: Toronto ON
Work Model: Hybrid (34 Days Work From Office)
Experience Required: 68 Years


Role Overview

We are seeking an experienced Data Engineer with a strong foundation in data management principles and hands-on expertise in building scalable data platforms. The ideal candidate will partner closely with IT and business stakeholders to analyze business technical and system requirements and deliver high-quality data solutions that support analytics reporting and regulatory needs across multiple lines of business.


Key Responsibilities

Data Engineering & Development

  • Design and develop software solutions for retrieving parsing and processing structured and unstructured data

  • Define and implement scalable ETL/ELT workflows for reporting and analytics

  • Develop scripts and programs to transform and convert data into usable formats

  • Contribute to technical design development and implementation of data-driven applications

  • Ensure code quality performance scalability and responsiveness of applications


Platform Operations & Support

  • Support project teams in scaling monitoring and operating data platforms for high availability and performance

  • Collaborate with internal teams to deliver software features provide production support and resolve defects

  • Participate in post-implementation reviews sharing learnings and driving continuous improvement


Data Governance Lineage & Metadata

  • Collect and maintain metadata and data lineage information across systems business processes and data domains

  • Develop and maintain system-level and attribute-level data lineage documentation including:

    • Data flow diagrams

    • Process maps

    • Metadata catalogs

  • Identify and document data transformations to ensure traceability and transparency of data flows

  • Oversee metadata repositories and ensure lineage documentation is accurate and up to date

  • Work across multiple teams to embed metadata and lineage activities into standard project delivery

  • Collaborate with data owners data stewards developers and production support teams to support data governance requirements


Required Skills & Qualifications

Must-Have Experience

  • 68 years of experience in data engineering or related roles

  • Minimum 4 years of hands-on experience in data lineage and metadata management

  • Strong data domain expertise in AML and Payments particularly within:

    • Retail & Commercial Banking

    • Capital Markets

    • Wealth Management

    • ITS / Financial Services


Technical Skills

  • Proficiency in Advanced SQL Python and other data querying languages

  • Strong experience with Big Data and Cloud Technologies including:

    • Spark Hadoop Hive Kafka

    • Snowflake Databricks

    • Azure Data Lake

    • Elasticsearch

  • Strong understanding of object-oriented design and functional programming concepts

  • Experience building and supporting high-performance scalable data platforms


Soft Skills

  • Strong analytical and problem-solving abilities

  • Excellent collaboration and communication skills

  • Ability to work across multiple teams and manage complex dependencies

  • Strong documentation and knowledge-sharing mindset


Preferred / Nice-to-Have

  • Experience working in regulated financial services environments

  • Exposure to enterprise data governance frameworks and tools




Required Skills:

Experience (Years): 4-6 Essential Skills: Work with project teams throughout the organization to design implement and manage CDN infrastructure using Akamai to ensure high availability performance and scalability for customer facing applications and business processes. Handle multiple priorities and assignments with excellence and precision. Be a part of a 24/7/365 organization (some after hours support is expected as part of normal on-call rotation). Directly support line of business development teams provide guidance to them on implementation and changes for customer facing applications Develop and maintain security protocols and measures to protect CDN infrastructure from cyber threats. Monitor and analyze network performance identifying and resolving issues to optimize content delivery of critical applications. Collaborate with cross-functional teams to integrate Akamai CDN solutions with existing systems and applications. Collaborate with information security teams to implement DDoS protection strategies and other security measures in the CDN. Provide technical support and guidance to clients and internal teams regarding CDN and security best practices. Work closely with vendor and professional service teams on delivery related activities and strategy. Qualifications: Bachelors degree in Computer Science Information Technology or a related field. OR similar work experience. Strong understanding of network protocols (HTTP/HTTPS DNS TCP/IP). Proven experience as a CDN Engineer or similar role with a strong focus on -depth knowledge of Content Delivery Network technologies including caching load balancing and content optimization. Excellent problem-solving skills and attention to detail. Strong communication and teamwork abilities. Experience supporting 24/7/365 customer facing applications at enterprise scale. Awareness and experience with cybersecurity tools and practices such as firewalls intrusion detection/prevention systems and encryption. Proficiency in scripting and automation (e.g. Python Bash) a plus. Relevant certifications (e.g. CISSP CEH) are a plus but not required.

Job Title: Data EngineerLocation: Toronto ON Work Model: Hybrid (34 Days Work From Office) Experience Required: 68 YearsRole OverviewWe are seeking an experienced Data Engineer with a strong foundation in data management principles and hands-on expertise in building scalable data platforms. The idea...
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Company Industry

IT Services and IT Consulting

Key Skills

  • Apache Hive
  • S3
  • Hadoop
  • Redshift
  • Spark
  • AWS
  • Apache Pig
  • NoSQL
  • Big Data
  • Data Warehouse
  • Kafka
  • Scala