Data Architect - Synapse Analytics (10-18 yrs)

RoleData Architect.

Skillset : PySpark, ADF and PowerBI.

Experience10yrs to 18yrs.

Location : ALL HCL Locations (3days work from office).

Notice period: Immediate to 15days.

Payroll Company: Response Informatics Ltd.

Job Summary :

- Experience as Data Architect with expertise in PySpark, Azure Data Factory (ADF), and Power BI to design and implement scalable data solutions that meet business requirements.

- The ideal candidate will have a strong background in data engineering, data integration, and data visualization, with a focus on creating efficient, reliable, and secure data pipelines and reporting solutions.

Key Responsibility

- Core Technical Skills.

- Data Engineering with PySpark.

- Extensive experience in developing and optimizing PySpark-based data pipelines.

- Medallion Architecture (Bronze, Silver, Gold Layers).

- Strong understanding of implementing and optimizing Medallion Architecture.

- Power BI Development.

- Proficiency in building interactive dashboards and data visualizations.

- Azure Data Factory (ADF).

- Expertise in building and orchestrating ETL/ELT workflows on Azure.

- Azure Synapse Analytics.

- Solid experience with managing and querying large datasets for analytics.

- Azure Data Lake (ADLS).

- Proficient in designing data lakes for structured and unstructured data storage.

- Azure Databricks.

- Strong knowledge of data engineering and advanced analytics workflows using Databricks.

- Architectural Knowledge.

- Data Modeling and Schema Design.

- Expertise in designing efficient schemas for structured and semi-structured datasets.

- Distributed Computing Concepts.

- Deep understanding of distributed data processing and optimization techniques.

- Cloud Data Architecture.

- Experience in architecting scalable and secure solutions on Azure Cloud.

- Data Governance and Compliance.

- Familiarity with implementing data governance and regulatory compliance frameworks.

- Automation & Optimization.

- CI/CD for Data Solutions.

- Experience in automating deployments and managing data pipelines.

- Performance Optimization for Data Workflows.

- Ability to fine-tune pipelines for low latency and high throughput.

- Leadership & Collaboration.

- Team Leadership and Mentorship.

- Ability to guide and mentor engineering teams in best practices and architectural design.

- Stakeholder Management.

- Proficiency in translating business requirements into technical solutions.

- Collaboration with Data Scientists and Analysts.

- Experience working cross-functionally to deliver data-driven insights.