Solution Architect - Data Engineering

Key Responsibilities :

- Lead the end-to-end design and implementation of data architectures, ensuring performance, scalability, security, and reliability.

- Act as a technical lead and mentor, guiding development teams through best practices in data engineering and architecture.

- Architect and implement robust data integration pipelines for structured and unstructured data sources.

- Collaborate with stakeholders to translate business requirements into technical data solutions.

- Drive architectural standards, governance, and best practices across data platforms.

- Ensure optimization of data processing, storage, and query performance.

- Oversee data security, access control, and compliance across cloud environments.

- Troubleshoot complex data issues and provide strategic technical direction.

- Review and optimize existing data platforms for scalability and cost efficiency.

Mandatory Technical Skills

- Python - Advanced programming and scripting (mandatory).

- Apache Spark - Hands-on experience in distributed data processing.

- Snowflake - Strong experience in data modeling, optimization, and performance tuning.

- SQL - Expert-level ability to write, debug, and optimize complex SQL queries.

- Cloud Platforms - AWS Azure Databricks (GCP exposure is a plus but not a primary focus)

Required Experience & Qualifications :

- 11+ years of hands-on experience as a Solution Architect and/or Data Engineer.

- Proven experience leading end-to-end data solution development, including design, implementation, and deployment.

- Strong background in cloud-native data architectures.

- Experience managing or mentoring development teams and driving delivery excellence.

- Expertise in performance tuning, scalability, and data security best practices.

- Ability to work cross-functionally with engineering, analytics, and business teams.

- Strong problem-solving and communication skills.

Nice to Have :

- Experience with real-time data processing and streaming platforms.

- Exposure to data governance, metadata management, and data quality frameworks.

- Prior experience in large-scale enterprise or regulated environments.