Sr Data Anaytics Engineer

Title: Sr Data Analytics Engineer
Location: Remote
Duration: 6+ months Extendable
Prioritize Profiles With:
Medallion Architecture (Bronze/Silver/Gold)
Data Product Ownership
Semantic Layer Design & Management
Databricks / Fabric / Snowflake
Data Lineage & Metadata Management
Data Governance & Domain Modeling
Curated Analytics-Ready Datasets
Strong SQL and Complex Transformations
Enterprise Analytics Engineering experience
Job Description:
Analytics Engineer Requirements:
Very strong SQL
Experience in ETL and complex data transformations
Strong attention to sematic modeling
Experience in 3-tier/medallion architectures
Understanding of warehouse modeling - fact and dimensions, star/snowflake schemas
Experience in BI tooling (understanding the data requirements for BI development and how data is sourced for BI)
Experience in Snowflake, Databricks, or similar cloud-native data warehouse
About the Role
This role focuses on designing, building, and maintaining business-ready data products within the Medallion Architecture, specifically the Gold and Semantic layers.
The position is responsible for transforming curated data into business-ready models, defining KPIs, business logic, and semantic structures, and delivering trusted, analytics-ready datasets and insights.
Key Responsibilities
Build and maintain business-ready data products and semantic models that translate curated enterprise data into accessible structures for analytics and reporting.
Design, develop, and maintain semantic layer datasets (e.g., models, views, tabular models) aligned with business logic, KPIs, and reporting standards.
Perform data transformations, aggregations, and modeling within the Gold/Presentation layer, applying business rules while maintaining data integrity and compliance.
Write and optimize complex SQL queries to support analytics, reporting performance, and data model efficiency.
Collaborate with enterprise data and governance teams to refine layer datasets, ensuring alignment between technical data structures and business requirements.
Identify and resolve data quality, performance, and model alignment issues in partnership with enterprise data and governance teams.
Resolve complex conflicts between business definitions, KPIs, and data models while ensuring consistency with enterprise standards.
Document data models, semantic layers, and analytics solutions, including business definitions, mappings, and technical specifications.
Contribute to the creation, maintenance, and evolution of Data Contracts, contextual data layers, and business ontologies, including:
Defining and documenting data meaning, lineage, and ownership
Aligning datasets to business domains, entities, and standardized definitions
Supporting the development of a context layer that enables consistent interpretation and reuse of data products across teams
Collaborate with cross-functional teams to deliver scalable and governed data products.
Ensure adherence to data governance, security, and regulatory compliance through validation, documentation, and alignment with enterprise standards.
Minimum Qualifications (Knowledge, Skills & Abilities)
Strong proficiency in SQL for data transformation, aggregation, and analysis.
Experience with Business Intelligence tools (e.g., Power BI) and semantic modeling.
Understanding of data modeling concepts, including star schema and dimensional modeling.
Experience working with curated datasets in the Gold/Presentation layer and analytics-ready data products.
Familiarity with data governance, data quality, and metadata management concepts.
Ability to translate business requirements into data models, KPIs, and analytics solutions.
Experience with modern cloud data platforms such as Snowflake, Azure, Databricks, or similar technologies.
Familiarity with version control and collaborative development practices (e.g., Git, GitHub, pull/merge request workflows).
Experience with CI/CD workflows and collaborative development methodologies.
Exposure to performance optimization within semantic models and reporting layers.
Strong analytical thinking, problem-solving, and stakeholder management skills.
Excellent communication skills with both technical and business audiences
EEO

Work arrangement
Yes