Solution Architect - Data Engineer (10-15 yrs)

Job Description :

- Minimum of10 years of experience in data architecture, with a focus on AWS cloud services.

- Strong experience in microservices architecture and designing scalable data solutions on AWS.

- Expertise with AWS technologies such as S3, Redshift, Athena, AWS Glue, etc.

- Strong communication skills and ability to collaborate with diverse teams.

- Experience in leading architectural decisions and mentoring technical teams.

- Experience in designing and implementing ETL pipelines using AWS tools (AWS Glue, Lambda, etc.).

- Strong data modeling skills, covering both relational and NoSQL databases.

- Solid understanding of data governance, data security, and compliance requirements.

- Proven experience optimizing data architectures for performance and cost efficiency.

- Excellent problem-solving skills and a strategic mindset for building efficient, resilient data solutions.

Key Responsibilities :

Data Architecture Design :

- Design and implement scalable, secure, and efficient data architectures for enterprise solutions using AWS.

- Develop data management strategies to support business intelligence, advanced analytics, and AI initiatives.

Cloud Data Solutions :

- Lead the development of AWS-based data ecosystems, utilizing services like AWS Data Lakehouse, S3, Redshift, Athena, and other AWS data technologies for data storage, processing, and analysis.

Microservices Architecture :

- Design and implement microservices-based architectures for data integration and distributed data processing, ensuring efficient communication and scalability.

Data Modelling and Integration :

- Design and implement data models (both relational and non-relational) to ensure scalability and performance.

- Integrate data from diverse sources, including databases, APIs, and real-time streaming.

ETL and Data Pipeline Architecture :

- Architect end-to-end ETL and data pipelines using tools like AWS Glue, Lambda, and other AWS services to facilitate data ingestion, transformation, and curation.

Data Governance and Security :

- Implement data governance policies to ensure compliance with industry standards for data security, privacy, and integrity.

- Leverage AWS security services, including IAM, encryption, and data masking to protect sensitive information.

Performance Optimization :

- Optimize the performance of data architectures and solutions, ensuring cost-effective data storage, retrieval, and processing while maintaining scalability.

Collaboration and Stakeholder Engagement :

- Work closely with cross-functional teams, including product development, data engineering, and business stakeholders, to align data architecture with business goals and objectives.

Emerging Technologies :

- Stay up-to-date with advancements in cloud technologies, data management, and data architecture.

- Drive the adoption of new tools, frameworks, and methodologies to improve the data landscape.

Leadership :

- Provide technical guidance and mentorship to data engineers and developers.

- Lead architectural discussions, reviews, and decision-making processes.