The Role
Design and maintain conceptual, logical, and physical data models using SQLDBM and Snowflake. Translate business requirements into production-ready schemas, generate and optimize DDL, manage schema versioning and drift detection, and maintain data dictionaries, metadata, and lineage. Collaborate with architects, engineers, analysts, and stakeholders on dimensional and relational modeling, data governance, query performance, indexing, and clustering strategies.
Summary Generated by Built In
Position Overview
Location - Bangalore/Pune/Chennai/Remote
Location - Bangalore/Pune/Chennai/Remote
We are seeking a skilled and detail-oriented Mid-Level Data Modeler to join our data
engineering and architecture team. In this role, you will bridge the gap between business
requirements and technical execution by designing, developing, and maintaining
conceptual, logical, and physical data models.
The ideal candidate has hands-on experience utilizing SQLDBM for cloud data warehouse
modeling (e.g., Snowflake) and possesses a deep understanding of modern data
architecture, normalization, and dimensional modeling techniques. You will collaborate
closely with data architects, analytics engineers, and business stakeholders to ensure our
data infrastructure is scalable, performant, and aligned with organizational goals.
Job Duties & Responsibilities
• Data Modeling & Design: Design and maintain end-to-end conceptual, logical, and
physical data models to support enterprise analytics and reporting initiatives.
• Platform Management: Utilize SQLDBM as the primary tool for cloud data
warehouse design, reverse-engineering existing databases, and maintaining up-to
date visual documentation.
• Architecture Collaboration: Work alongside Data Architects to implement robust
architectural standards, establish data symbology, and support asset classification
or master data management frameworks.
• Pipeline Support: Collaborate with data engineers and business analysts to
translate complex business requirements (BRDs/RDDs) into clean, production
ready schema designs.
• Forward/Reverse Engineering: Generate, review, and optimize DDL scripts from
SQLDBM for deployment, and manage schema versioning and drift detection.
• Data Governance: Maintain data dictionaries, definitions, and metadata registries
within SQLDBM to ensure data lineage and governance standards are strictly
followed.
• Performance Tuning: Assist in optimizing SQL queries, indexing strategies, and
clustering keys to ensure high-performance data retrieval.
Requirements
Must-Have
• Experience: 3–5 years of professional experience in data modeling, data
architecture, or data engineering.
• Tooling: Strong, hands-on proficiency with SQLDBM for visual modeling, schema
generation, and collaboration.
• Methodologies: Proven expertise in Dimensional Modeling (Kimball/Star
Schema) as well as relational modeling (3NF).
• Technical Skills: Advanced SQL skills for querying, data profiling, and analyzing
complex data sets.
• Cloud Data Platforms: Direct experience modeling for modern cloud data
warehouses, specifically Snowflake.
• Documentation: Proven track record of translating business needs into structured
technical documentation and maintaining comprehensive data dictionaries.
Nice-to-Have (Preferred Qualifications)
• Version Control: Experience integrating SQLDBM with Git repositories
(GitHub/GitLab) for database schema CI/CD pipelines.
• Domain Knowledge: Experience working within Financial Services, Wealth
Management, or FinTech sectors (understanding of security master systems or
portfolio accounting data is a major plus).
• Programming: Familiarity with Python for data manipulation or automated testing.
• Agile Frameworks: Experience working in an Agile/Scrum development
environment.
• Certifications: Snowflake Certified Core Support, SnowPro Core, or relevant data
modeling certifications.
Skills Required
- 3-5 years of professional experience in data modeling, data architecture, or data engineering
- Hands-on proficiency with SQLDBM for visual modeling, schema generation, and collaboration
- Expertise in dimensional modeling, including Kimball and Star Schema techniques
- Expertise in relational modeling using 3NF
- Advanced SQL skills for querying, data profiling, and analyzing complex datasets
- Experience modeling for cloud data warehouses, specifically Snowflake
- Experience translating business needs into technical documentation and maintaining data dictionaries
- Experience integrating SQLDBM with Git repositories such as GitHub or GitLab for database schema CI/CD pipelines
- Experience in Financial Services, Wealth Management, or FinTech, particularly security master or portfolio accounting data
- Familiarity with Python for data manipulation or automated testing
- Experience in an Agile or Scrum development environment
- Snowflake Certified Core Support, SnowPro Core, or relevant data modeling certification
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The Company
What We Do
Blackbuck Insights is a global data and AI consultancy providing data engineering services, cloud modernization, AI activation, and platform operations. The company helps enterprises modernize legacy environments, migrate and scale data platforms, build AI-enabled business applications, and establish trusted data foundations for analytics and intelligent decision-making. Its services support organizations seeking reliable, performant, and scalable technology solutions.
