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Data Modeler

  • Toronto, ON, Canada

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Original job description

Greetings!

Iris’s leading financial client is looking for Data Modeler to join their team at Toronto, ON(Hybrid) location.

Job Title: Data Modeler

Location: Toronto, ON(Hybrid)

Duration: Long Term

Job Description:

  • Years of experience in Data Modeling, Database Design, Data Warehousing, or Enterprise Data Platforms.
  • Strong proficiency in conceptual, logical, physical, relational, and dimensional data modeling.
  • Hands-on experience with data modeling tools such as ERwin, ER/Studio, PowerDesigner, or equivalent.
  • Strong SQL skills for data analysis, profiling, validation, and query optimization.
  • Experience working with databases and cloud data platforms such as Oracle, SQL Server, PostgreSQL, Snowflake, Amazon Redshift, or equivalent.
  • Good understanding of DataOps principles, including automated data pipelines, data quality, metadata management, lineage, monitoring, and repeatable onboarding processes.
  • Experience with ETL/ELT processes, source-to-target mappings, data integration, and data warehousing architectures.
  • Understanding of data governance, master/reference data, data security, and regulatory compliance considerations.
  • Experience collaborating with Solution Architects, Data Engineers, application teams, and business stakeholders in Agile delivery environments.
  • Strong analytical, problem-solving, documentation, and communication skills.

About Iris Software Inc.

With 4,000+ associates and offices in India, U.S.A. and Canada, Iris Software delivers technology services and solutions that help clients complete fast, far-reaching digital transformations and achieve their business goals. A strategic partner to Fortune 500 and other top companies in financial services and many other industries, Iris provides a value-driven approach - a unique blend of highly-skilled specialists, software engineering expertise, cutting-edge technology, and flexible engagement models. High customer satisfaction has translated into long-standing relationships and preferred-partner status with many of our clients, who rely on our 30+ years of technical and domain expertise to future-proof their enterprises. Associates of Iris work on mission-critical applications supported by a workplace culture that has won numerous awards in the last few years, including Certified Great Place to Work in India; Top 25 GPW in IT & IT-BPM; Ambition Box Best Place to Work, #3 in IT/ITES; and Top Workplace NJ-USA.

More about this job

Responsibilities

Design and support conceptual, logical, physical, relational, and dimensional data models for databases, data warehouses, and enterprise data platforms. Collaborate with architects, engineers, application teams, and business stakeholders on data integration, quality, governance, and DataOps processes.

Requirements

The role requires experience in data modeling, database design, data warehousing, or enterprise data platforms, along with proficiency in SQL and data modeling tools such as ERwin, ER/Studio, or PowerDesigner. Candidates should understand cloud and relational databases, ETL/ELT, DataOps, governance, security, and regulatory compliance, and have strong analytical, documentation, and communication skills.

Skills

  • Data Modeling
  • Database Design
  • Data Warehousing
  • Conceptual Data Modeling
  • Logical Data Modeling
  • Physical Data Modeling
  • Relational Data Modeling
  • Dimensional Data Modeling
  • SQL
  • Data Profiling
  • Query Optimization
  • DataOps
  • ETL/ELT
  • Data Integration
  • Data Governance
  • Data Quality

Visa sponsorship

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Categories

  • Data & Analytics
  • Technology
  • Software
  • Finance & Accounting

Keywords

  • Data Modeling
  • Database Design
  • Data Warehousing
  • Enterprise Data Platforms
  • Conceptual Data Modeling
  • Logical Data Modeling
  • Physical Data Modeling
  • Relational Data Modeling
  • Dimensional Data Modeling
  • ERwin
  • ER/Studio
  • PowerDesigner
  • SQL
  • Oracle
  • SQL Server
  • PostgreSQL
  • Snowflake
  • Amazon Redshift
  • DataOps
  • Automated Data Pipelines
  • Data Quality
  • Metadata Management
  • Data Lineage
  • ETL/ELT
  • Source-to-Target Mapping
  • Data Integration
  • Data Governance
  • Master Data
  • Reference Data
  • Agile

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