Technology Stack
- Azure Data Lake
- Azure Synapse Analytics
- Azure Data Lake (Azure Data Stack preferred)
Role Summary
We are seeking a seasoned Data Engineer with strong data architecture experience to lead data analysis, data repository design, and end-to-end data pipeline architecture. The role is a key part of the organization’s cloud, big data, and AI adoption journey, contributing to the design and implementation of a centralized data repository and analytics platform for sovereign and country risk data.
The candidate is expected to bring strong business acumen, technical leadership, and an innovation mindset while working across multi-location and multi-vendor teams.
Scope of Work & Responsibilities
Business Engagement, Data Discovery & Value Creation
- Engage with business stakeholders to gather data, reporting, and analytics requirements.
- Document data flows, data mappings, usage patterns, and exceptions.
- Identify opportunities where data and analytics solutions drive measurable business value.
- Translate business needs into scalable data architectures and value streams.
Solution Design & Technical Leadership
- Design and architect robust, scalable, high-performance data solutions on cloud-native and hybrid platforms.
- Create architecture blueprints for data storage, access, governance, and management.
- Write technical specifications and contribute to testing artifacts when required.
- Lead or support solution development with clean, maintainable, well-documented code.
- Write and optimize complex SQL queries across relational and non-relational data stores.
- Design efficient ETL/ELT workflows for accurate data movement between systems.
Data Platform & Engineering
- Work with multiple data platforms including:
- Relational databases (Oracle, SQL)
- Azure Data Lake
- Azure Blob Storage
- Azure Synapse Analytics
- Design and build analytical and reporting-focused data repositories.
- Optimize large-scale data models for performance and scalability.
- Contribute to metadata management, data lineage, and impact analysis initiatives.
Required Skills & Experience Must-Have Skills
- 6–7+ years of experience in Data Engineering with exposure to Data Architecture.
- Strong experience in:
- Data modeling and ETL design
- Data repository architecture
- Data discovery and data mapping
- Technologies:
- SQL, Oracle
- Azure Data Lake (Azure Data Stack preferred)
- Python
- ETL tools
- Familiarity with big data technologies such as Spark and Kafka.
Skills: data engineer,etl,azure data lake,azure data,databricks,azure data services,azure synapse,databricks certified,azure sql database,microsoft certified