Mid-Level Data Modeler (SQLDBM)
Position Overview
Location \- Bangalore/Pune/Chennai/Remote<\/div>
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Location \- Bangalore/Pune/Chennai/Remote<\/div>
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We are seeking a skilled and detail\-oriented Mid\-Level Data Modeler to join our data \nengineering and architecture team. In this role, you will bridge the gap between business \nrequirements and technical execution by designing, developing, and maintaining \nconceptual, logical, and physical data models. \nThe ideal candidate has hands\-on experience utilizing SQLDBM for cloud data warehouse \nmodeling (e.g., Snowflake) and possesses a deep understanding of modern data \narchitecture, normalization, and dimensional modeling techniques. You will collaborate \nclosely with data architects, analytics engineers, and business stakeholders to ensure our \ndata infrastructure is scalable, performant, and aligned with organizational goals.
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Job Duties & Responsibilities
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\u2022 Data Modeling & Design: Design and maintain end\-to\-end conceptual, logical, and \nphysical data models to support enterprise analytics and reporting initiatives.
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\u2022 Platform Management: Utilize SQLDBM as the primary tool for cloud data \nwarehouse design, reverse\-engineering existing databases, and maintaining up\-to\ndate visual documentation.
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\u2022 Architecture Collaboration: Work alongside Data Architects to implement robust \narchitectural standards, establish data symbology, and support asset classification \nor master data management frameworks.
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\u2022 Pipeline Support: Collaborate with data engineers and business analysts to \ntranslate complex business requirements (BRDs/RDDs) into clean, production\nready schema designs.
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\u2022 Forward/Reverse Engineering: Generate, review, and optimize DDL scripts from \nSQLDBM for deployment, and manage schema versioning and drift detection.
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\u2022 Data Governance: Maintain data dictionaries, definitions, and metadata registries \nwithin SQLDBM to ensure data lineage and governance standards are strictly \nfollowed.
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\u2022 Performance Tuning: Assist in optimizing SQL queries, indexing strategies, and \nclustering keys to ensure high\-performance data retrieval.
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Requirements<\/h3>
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Requirements<\/h3>Must\-Have
<\/div>\u2022 Experience: 3\u20135 years of professional experience in data modeling, data \narchitecture, or data engineering.
<\/div>\u2022 Tooling: Strong, hands\-on proficiency with SQLDBM for visual modeling, schema \ngeneration, and collaboration.
<\/div>\u2022 Methodologies: Proven expertise in Dimensional Modeling (Kimball/Star \nSchema) as well as relational modeling (3NF).
<\/div>\u2022 Technical Skills: Advanced SQL skills for querying, data profiling, and analyzing \ncomplex data sets.
<\/div>\u2022 Cloud Data Platforms: Direct experience modeling for modern cloud data \nwarehouses, specifically Snowflake.
<\/div>\u2022 Documentation: Proven track record of translating business needs into structured \ntechnical documentation and maintaining comprehensive data dictionaries.
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<\/div>Nice\-to\-Have (Preferred Qualifications)
<\/div>\u2022 Version Control: Experience integrating SQLDBM with Git repositories \n(GitHub/GitLab) for database schema CI/CD pipelines.
<\/div>\u2022 Domain Knowledge: Experience working within Financial Services, Wealth \nManagement, or FinTech sectors (understanding of security master systems or \nportfolio accounting data is a major plus).
<\/div>\u2022 Programming: Familiarity with Python for data manipulation or automated testing.
<\/div>\u2022 Agile Frameworks: Experience working in an Agile/Scrum development \nenvironment.
<\/div>\u2022 Certifications: Snowflake Certified Core Support, SnowPro Core, or relevant data \nmodeling certifications.
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\u2022 Experience: 3\u20135 years of professional experience in data modeling, data \narchitecture, or data engineering.
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\u2022 Tooling: Strong, hands\-on proficiency with SQLDBM for visual modeling, schema \ngeneration, and collaboration.
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\u2022 Methodologies: Proven expertise in Dimensional Modeling (Kimball/Star \nSchema) as well as relational modeling (3NF).
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\u2022 Technical Skills: Advanced SQL skills for querying, data profiling, and analyzing \ncomplex data sets.
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\u2022 Cloud Data Platforms: Direct experience modeling for modern cloud data \nwarehouses, specifically Snowflake.
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\u2022 Documentation: Proven track record of translating business needs into structured \ntechnical documentation and maintaining comprehensive data dictionaries.
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Nice\-to\-Have (Preferred Qualifications)
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\u2022 Version Control: Experience integrating SQLDBM with Git repositories \n(GitHub/GitLab) for database schema CI/CD pipelines.
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\u2022 Domain Knowledge: Experience working within Financial Services, Wealth \nManagement, or FinTech sectors (understanding of security master systems or \nportfolio accounting data is a major plus).
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\u2022 Programming: Familiarity with Python for data manipulation or automated testing.
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\u2022 Agile Frameworks: Experience working in an Agile/Scrum development \nenvironment.
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\u2022 Certifications: Snowflake Certified Core Support, SnowPro Core, or relevant data \nmodeling certifications.
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