
Semantic Layer
6 days ago
Role & responsibilities
Job Summary:
We are looking for a skilled Data Engineer / BI Developer with experience in designing and managing the semantic layer for business intelligence platforms and performing historical data loads for analytical systems. This role will support enterprise data models, enhance reporting efficiency, and ensure consistent and reliable access to historical data for decision-making.
Key Responsibilities:
Semantic Layer Development
- Design and implement a semantic layer using tools like Tableau, Power BI, Looker, SAP BO, or custom views.
- Translate business requirements into logical models that abstract complex data into user-friendly, business-oriented terms.
- Define business metrics, dimensions, hierarchies, and calculated fields to support consistent analytics.
- Optimize semantic layer performance for large-scale reporting and self-service BI.
Historical Data Loading
- Design and implement processes for initial and incremental historical data loads into data warehouses or data lakes.
- Use ETL/ELT tools (e.g., Informatica, Talend, DBT, Azure Data Factory, AWS Glue) to load and transform large historical datasets.
- Ensure data accuracy, versioning, and maintain proper data lineage for historical records.
- Implement and maintain SCD (Slowly Changing Dimensions) and time-based data tracking logic.
General Responsibilities
- Collaborate with data modelers, analysts, and business stakeholders to define semantic and data retention requirements.
- Document semantic models and historical data load processes.
- Troubleshoot data issues and support UAT and production deployments.
- Ensure compliance with data governance and data quality standards.
Required Skills & Qualifications:
- Bachelors degree in Computer Science, Information Systems, or related field.
- 4+ years of experience in data engineering or BI development.
- Hands-on experience with semantic modeling tools (Tableau semantic layer, Power BI datasets, LookML, etc.).
- Proficient in SQL, data modeling, and ETL/ELT pipelines.
- Experience with historical data handling techniques, including SCD Type 1/2, snapshots, and time-series data.
- Familiarity with data warehouse technologies (Snowflake, Redshift, BigQuery, etc.).
- Strong communication and documentation skills.
Preferred Qualifications:
- Experience with data virtualization or BI metadata management tools.
- Cloud platform experience (AWS, Azure, or GCP).
- Understanding of data governance, security, and compliance frameworks.
- Knowledge of Agile/Scrum project methodologies.
Preferred candidate profile
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