Data & Analytics

You will be responsible for defining enterprise-grade data architecture, leading analytics initiatives, and ensuring the delivery of scalable, high-quality data solutions. Working closely with business stakeholders, engineering teams, and governance functions, you will transform complex data landscapes into actionable insights and business outcomes.

Mandatory Skills

• Data Architecture & Data Modeling
• Data Engineering, ETL/ELT & Data Integration
• Data Warehousing & Lakehouse Architecture
• Data Governance, Data Quality & MDM
• Data Analysis, Profiling & Transformation
• Business Intelligence & Data Visualization
• Statistical Analysis & Advanced Analytics
• SQL, Python, PySpark & Big Data Processing
• Cloud Data Platforms & Analytics Ecosystems
• Data Security, Privacy & Compliance
• DataOps, CI/CD & Automation
• Stakeholder Management & Technical Leadership

 

Preferred Technologies

Data Platforms & Cloud:
Microsoft Fabric, Azure Synapse Analytics, Azure Data Factory, Azure Databricks, Azure Data Lake Storage, Snowflake

Data Engineering & Big Data:
Apache Spark, Databricks, Kafka, Hadoop

Databases:
SQL Server, Azure SQL Database, PostgreSQL, Oracle, Cosmos DB

Analytics & Visualization:
Power BI, Tableau, Qlik Sense

Data Governance & Quality:
Microsoft Purview, Collibra, Informatica Data Quality, Great Expectations

Programming & Analytics:
SQL, Python, PySpark, Pandas, NumPy, Scikit-learn

DevOps & Collaboration:
Azure DevOps, GitHub, GitHub Actions, Docker, Jira, Confluence

• Define, design, and own end-to-end scalable data architectures from concept through production deployment.
• Collaborate with compliance, privacy, risk, information security, operations, and platform teams to ensure all business and regulatory requirements are addressed.
• Develop and implement strategies for data governance, metadata management, master data management, data quality, and data security.
• Provide technical leadership and advocate best practices for data architecture, engineering, and analytics initiatives.
• Establish reusable standards, frameworks, and design patterns across the data ecosystem.
• Lead data analysis and profiling activities, including data quality assessment, transformation rules, and integration requirements.
• Design, document, and maintain conceptual, logical, and physical data models.
• Oversee the complete data lifecycle, ensuring effective design, development, validation, documentation, and continuous improvement.
• Conduct advanced analytics to identify trends, generate actionable insights, and measure business performance.
• Develop impactful dashboards and visualizations that enable informed decision-making.
• Apply statistical techniques and analytical models to solve complex business challenges.
• Collaborate with data engineers, data scientists, and business stakeholders to deploy scalable analytics solutions.
• Drive analytical excellence, ensure solution quality, and lead successful delivery across projects.
• Organize, transform, and analyze large-scale structured and unstructured datasets to unlock business value.
• Define and continuously improve standards for data analysis, reporting, and analytics delivery.=

Opportunity to build enterprise-scale data and analytics solutions that drive measurable business impact.Exposure to modern cloud data platforms, advanced analytics, and AI-driven innovation.Collaborative environment with architects, engineers, analysts, and business leaders.Continuous learning through cutting-edge technologies and challenging projects.Flexible work environment that encourages innovation, ownership, and professional growth