Big Data Engineer

We are seeking a highly skilled and experienced Senior Data Warehouse Developer to design, develop, and optimize our enterprise data warehouse solutions. This role requires strong technical expertise in data modeling, ETL and semantic layer development, basic SQL performance tuning with a focus on building scalable, secure, and high-performing data platforms. The ideal candidate will combine deep expertise in data modeling, architecture, and integration with the ability to collaborate across business and technology teams.

Please apply, If you have the passion and standard methodologies work in an environment where challenges are a norm, where individual brilliance is valued and goes hand in hand with team performance, Where being proactive is how we do things !!!

Responsibilities :

Key Responsibilities

• Lead the design and development of logical, and physical data models for the enterprise data warehouse and analytics platforms.
• Define and enforce standards for dimensional modeling, normalization, star schemas, snowflake schemas.
• Ensure models support business intelligence, reporting, and advanced analytics use cases.
• Establish and promote data modeling and warehouse best practices, standards, and methodologies.
• Support data governance initiatives, ensuring consistency, accuracy, and compliance across the enterprise.
• Architect scalable data warehouse solutions (cloud, or hybrid).
• Partner with ETL/ELT developers to ensure alignment between models and pipelines.

Core Qualifications

• Strong experience in data architecture, data modeling, and data warehouse design.
• Strong expertise in logical, and physical data modeling using tools like ERwin, PowerDesigner, or equivalent.
• Deep knowledge of relational databases and SQL performance optimization.
• Familiarity with data integration and ETL/ELT data pipeline.
• Strong knowledge of dimensional modeling (Kimball/Inmon) methodologies.
• Strong expertise with BI/reporting platforms (OAC, Tableau, Power BI).

Preferred experience

• Knowledge of data lake-house architectures and big data ecosystems (Databricks, Spark, Hadoop).
• Hands-on experience with cloud data warehouses (Snowflake, Redshift, BigQuery, Azure Synapse, etc.).
• Experience with metadata management and data catalog tools.
• Exposure to master data management (MDM) and data governance practices.