Senior Data & BI Developer

Sanas is pioneering the future of human communication. Founded by a team of Stanford researchers and entrepreneurs with deep industry experience, Sanas has developed the world's first real-time speech AI platform capable of accent translation, noise cancellation, speech enhancement, cross-language communication, and more.

Sanas makes conversations clearer, more inclusive, and more effective, removing barriers that prevent people from being understood, regardless of accent, background noise, or native language.

Sanas is currently one of the fastest growing startups in Silicon Valley, growing from $16M to $50M ARR in 2025. The company's core business is profitable and is on track to end 2026 with >$77M ARR. Our team combines deep expertise in model innovation and systems engineering with a design-minded product engineering culture to build and ship cutting-edge AI models and experiences — entirely in-house.

Sanas is a 130 person team, established in 2020. In this short span, we've successfully secured over $100 million in funding. Our innovation has been supported by the industry's leading investors, including Insight Partners, Google Ventures, Quadrille Capital, General Catalyst, Quiet Capital, and other influential investors. Our reputation is further solidified by collaborations with numerous Fortune 100 companies. With Sanas, you're not just adopting a product; you're investing in the future of communication.

If you’re looking to have a significant role in roadmapping and driving technical directions, if you’re looking to deploy challenging and big ideas without much overhead or slowness, if you're looking to leave your mark on an ambitious, generational mission to change how the worlds thinks about speech + AI, then Sanas is a well-suited place for you.

About the role
We are looking for a Data & BI Developer with 5-7 years of experience to build scalable data  solutions and deliver business intelligence solutions using Microsoft Fabric and Power BI. 

The role requires a strong combination of data engineering, ETL/ELT, Lakehouse development, data  modeling, semantic modeling, and Power BI. Candidate should be comfortable working across the  complete data lifecycle (Source data to BI Layer)

What you'll do

1. Data Engineering & Microsoft Fabric 

• Develop data pipelines using Fabric Data Factory / Data Pipelines. 

• Build and manage Lakehouse-based data platforms. 

• Work with OneLake, Lakehouse, Data Warehouse, Notebooks, Spark, and SQL. • Implement Bronze, Silver, Gold / Curated data layers. 

• Build reusable and scalable data ingestion and transformation processes. 

• Work with structured and semi-structured data from multiple source systems. • Implement incremental loads, historical data processing, and data refresh strategies. • Monitor and troubleshoot data pipelines and resolve failures. 

2. ETL / ELT & Data Transformation 

• Develop robust ETL/ELT pipelines for data ingestion and transformation. 

• Perform data cleansing, validation, standardization, and enrichment. 

• Develop transformations using SQL and PySpark/Python. 

• Implement appropriate error handling, logging, and monitoring. 

• Optimize pipeline performance and processing time. 

• Support large datasets and historical data requirements. 

3. Data Modeling & Data Mart Development 

• Develop fact and dimension tables using star-schema principles. 

• Build analytical data marts for different business domains. 

• Apply appropriate normalization and denormalization techniques. 

• Create reusable and trusted datasets for BI and analytics. 

• Ensure consistent business logic and KPI definitions. 

• Work with stakeholders to translate business requirements into appropriate data models.

4. Power BI & BI Development 

• Design and develop Power BI dashboards and reports. 

• Develop optimized Power BI semantic models.

• Build appropriate relationships between fact and dimension tables.

• Develop DAX measures, calculated columns, and KPIs. 

• Use Power Query for data preparation where required. 

• Implement appropriate Power BI visualization and dashboard design. 

• Develop drill-downs, drill-throughs, filters, tooltips, bookmarks, and interactive reporting  experiences. 

• Optimize Power BI reports and semantic models for performance. 

• Work with stakeholders to understand reporting and analytical requirements. • Convert business requirements into meaningful dashboards and insights.. 

5. Data Quality & Governance 

• Implement data quality checks within pipelines and data models. 

• Identify and resolve data completeness, accuracy, duplication, and consistency issues. • Ensure data used in dashboards is reliable and traceable. 

• Maintain appropriate documentation for data pipelines, models, KPIs, and business rules. • Follow enterprise data security and governance standards. 

Qualifications

Data Engineering 

• 5–7 years of relevant experience in Data Engineering / BI development. • Strong SQL skills. 

• Hands-on experience with ETL/ELT. 

• Experience with Microsoft Fabric or similar modern data platforms. 

• Experience with Fabric Data Pipelines / Data Factory. 

• Experience with Lakehouse architecture. 

• Understanding of Medallion Architecture. 

• Experience with SQL and PySpark/Python. 

• Experience working with large datasets and historical data. 

• Understanding of data quality and pipeline monitoring. 

BI & Power BI 

• Strong hands-on experience with Power BI. 

• Strong understanding of Power BI semantic models. 

• Good knowledge of DAX. 

• Good knowledge of Power Query / M. 

• Strong understanding of star schema and dimensional modeling. 

• Experience developing fact and dimension models. 

• Experience designing executive and operational dashboards. 

• Understanding of Power BI performance optimization. 

• Knowledge of Import, DirectQuery, and Direct Lake concepts. 

• Experience implementing row-level security is a plus. 

Core Skill Profile

Data Engineering: Microsoft Fabric | Data Pipelines | ETL/ELT | Lakehouse | Medallion Architecture |  SQL | PySpark/Python 

Data Modeling: Star Schema | Fact & Dimensions | Data Marts | Golden/Curated Layer | Semantic  Models 

BI: Power BI | DAX | Power Query | KPI Development | Dashboard Design | Performance Optimization