Design, implement, and maintain reliable, scalable, and secure data pipelines.
Ensure data ingestion, transformation, and availability from multiple sources.
Define and maintain data architectures focused on Analytics, BI, and AI.
Ensure data quality, consistency, governance, and traceability.
Design and provide analytical data models for consumption by BI tools.
Develop dashboards, reports, and strategic KPIs using Power BI.
Ensure adherence to data visualization best practices and report performance.
Optimize performance and cost of data solutions in on-premises and cloud environments.
Support BI, Analytics, AI, and business teams in efficient use of data and dashboards.
Produce technical documentation and evidence of delivered work.
Meet deadlines, targets, and contractual obligations.
Requirements
Solid experience in Data Engineering.
Advanced knowledge of Microsoft SQL Server (2022 or later) and T-SQL.
Experience in analytical data modeling (Data Warehouse, Data Mart, dimensional models).
Experience with ETL/ELT processes and data pipelines.
Familiarity with Microsoft data tools and services (Azure Data Factory, Azure Synapse, Azure Data Lake, Azure SQL).
Experience integrating and ingesting data from transactional systems, APIs, and files.
Hands-on experience creating dashboards and reports in Power BI.
Knowledge of DAX, Power Query, and semantic modeling.
Basic understanding of data preparation for AI and Machine Learning projects.
Experience with version control, automation, and CI/CD for data.
Knowledge of data security, governance, and access control.
Ability to work in high-volume data environments with high availability.
Bachelor's degree in Systems Analysis, Computer Science, Data Processing, Information Systems, Information Technology, Computer Engineering, or related fields.
Tech Stack
Azure
Cloud
ETL
MS SQL Server
SQL
Benefits
Prudential insurance: life insurance, funeral assistance, and birth package (as per insurer terms).
Birthday day off: time off on the birthday or during the birthday month.
Absence days: after one year of employment, possibility of up to 22 business days of absence without loss of pay, subject to prior notice for workload planning.