Senior/Principal Data Modeler

We’re looking for a seasoned Senior Data Modeler with strong expertise in enterprise data modeling and cloud technologies. In this role, you’ll help shape robust, scalable data solutions for complex business domains including customer, sales, finance, supplier, and retail. You’ll work alongside a skilled cross-functional team in a dynamic, cloud-first environment focused on innovation, governance, and agility. Ideal candidates bring deep knowledge in data modeling tools, cloud platforms, and metadata management. This is an opportunity to drive real impact on high-visibility projects with a collaborative and growing team.

Responsibilities:

Independently complete conceptual, logical and physical data models for any supported platform, including SQL Data Warehouse, Spark, Data Bricks Delta Lakehouse or other Cloud data warehousing technologies.

Governs data design/modelling – documentation of metadata (business definitions of entities and attributes) and constructions database objects, for baseline and investment funded projects, as assigned.

Develop a deep understanding of the business domains like Customer, Sales, Finance, Supplier, and enterprise technology inventory to craft a solution roadmap that achieves business objectives, maximizes reuse.

Drive collaborative reviews of data model design, code, data, security features to drive data product development.

Show expertise for data at all levels: low-latency, relational, and unstructured data stores; analytical and data lakes; SAP Data Model.

Develop reusable data models based on cloud-centric, code-first approaches to data management and data mapping.

Partner with the data stewards team for data discovery and action by business customers and stakeholders.

Provides and/or supports data analysis, requirements gathering, solution development, and design reviews for enhancements to, or new, applications/reporting.

Assist with data planning, sourcing, collection, profiling, and transformation.

Support data lineage and mapping of source system data to canonical data stores.

Create Source to Target Mappings (STTM) for ETL and BI developers.

Min requirements:

10+ years of overall technology experience that includes at least 8+ years of data modeling and systems architecture.

5+ years of experience with Data Lake Infrastructure, Data Warehousing, and Data Analytics tools.

6+ years of experience developing enterprise data models.

4+ years in cloud data engineering experience in at least one cloud (Azure, AWS, GCP).

4+ years of experience with building solutions in the retail or in the supply chain space.

Expertise in data modeling tools (ER/Studio, Erwin, IDM/ARDM models, CPG / Manufacturing/Sales/Finance/Supplier/Customer domains )

Experience with at least one MPP database technology such as Databricks Lakehouse, Redshift, Synapse, Teradata, or Snowflake.

Experience with version control systems like GitHub and deployment & CI tools.

Experience of metadata management, data lineage, and data glossaries is a plus.

Working knowledge of agile development, including DevOps and DataOps concepts.

Working knowledge of SAP data models, particularly in the context of HANA and S/4HANA, Retails Data like IRI, Nielsen Retail.

What we offer:

Opportunity to work on cutting-edge projects

Work with a highly motivated and dedicated team

Competitive salary

Flexible schedule

Benefits package - medical insurance, vision, dental, etc.

Corporate social events

Professional development opportunities

Well-equipped office

NB:

Placement and Staffing Agencies need not apply. We do not work with C2C at this time.

At this moment, we are not able to process H1B transfers. Applicants with CPT and OPT visas are welcome to apply.

About Us:

Grid Dynamics (Nasdaq: GDYN) is a digital-native technology services provider that accelerates growth and bolsters competitive advantage for Fortune 1000 companies. Grid Dynamics provides digital transformation consulting and implementation services in omnichannel customer experience, big data analytics, search, artificial intelligence, cloud migration, and application modernization. Grid Dynamics achieves high speed-to-market, quality, and efficiency by using technology accelerators, an agile delivery culture, and its pool of global engineering talent. Founded in 2006, Grid Dynamics is headquartered in Silicon Valley with offices across the US, UK, Netherlands, Mexico, and Central and Eastern Europe.

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