Data Architect - Business Intelligence (5-8 yrs)

Role Description :

As a Data Architect / BI Analyst / Data Analyst, you will be responsible for analyzing complex datasets, developing insightful reports, and ensuring data integrity across various systems. You will play a crucial role in bridging the gap between business needs and technical data solutions, facilitating data-driven strategies and improvements.

Responsibilities :

- Analyze financial, operational, and customer data to identify trends, patterns, and insights.

- Develop interactive dashboards and reports using Power BI to visualize data and communicate findings.

- Monitor key business metrics and provide data-driven recommendations to stakeholders.

- Ensure data accuracy and consistency across different reporting systems and platforms.

- Work on mid to large-scale Data Warehouse projects, contributing to the design, development, and maintenance of data warehousing solutions.

- Collaborate with data teams to ensure smooth data integration and transformation processes.

- Understand and document the data lifecycle, metadata, and data lineage.

- Collaborate with business teams to understand data and reporting requirements, translating them into technical specifications.

- Work closely with stakeholders to define reporting needs and ensure data accuracy.

- Act as a liaison between business and technical teams.

- Utilize the Microsoft data stack, including Synapse, SQL, Data Lake, Fabric, Databricks, and Power BI, to build and maintain data solutions.

- Develop and optimize SQL queries for data extraction, transformation, and analysis.

- Design and implement data models and data pipelines.

- Maintain data documentation and reporting standards to support governance and compliance.

- Ensure adherence to data security and privacy policies.

- Contribute to the development and implementation of data governance frameworks.

Qualifications :

Experience :

- 5+ years of experience in data analysis, business intelligence, data architecture, or related fields.

- Strong proficiency in SQL and experience with relational databases.

- Extensive experience with the Microsoft data stack (Synapse, SQL, Data Lake, Fabric, Databricks, Power BI).

- Understanding of data lifecycle, metadata management, and data lineage.

- Experience in analyzing financial, operational, and customer data.

- Knowledge of data modeling and ETL/ELT processes.