Data bricks Architect
- Zensar
- 14 - 24 years
- Hyderabad
- 6 months ago
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Job Description
Key Responsibilities:
- Platform Architecture Design: Lead the design and architecture of the digital platform, ensuring that the data infrastructure is scalable, secure, and reliable. Focus on utilizing AWS services (e.g., S3, Redshift, Glue, Lambda, Kinesis) and Databricks to build a robust, cloud-based data architecture.
- Data Integration & ETL Pipelines: Architect and implement ETL/ELT pipelines to integrate data from multiple sources (e.g., transactional databases, third-party services, APIs) into the platform, using AWS Glue, Databricks, and other tools for efficient data processing.
- Cloud Strategy & Deployment: Implement cloud-native solutions, leveraging AWS tools and Databricks for data storage, real-time processing, machine learning, and analytics. Design the platform to be cost-efficient, highly available, and easily scalable.
- Data Modelling: Develop and maintain data models for the platform that support business intelligence, reporting, and analytics. Ensure the data model design aligns with business requirements and the overall architecture of the platform.
- Machine Learning & Analytics Enablement: Work with data scientists and analysts to ensure that the architecture supports advanced analytics and machine learning workflows, enabling faster time to insights and model deployment.
- Data Security & Governance: Implement data governance frameworks to ensure data privacy, compliance, and security in the digital platform. Use AWS security tools and best practices to safeguard sensitive data and manage access control.
- Platform Performance & Optimization: Monitor and optimize platform performance, including the efficiency of data processing, data retrieval, and analytics workloads. Ensure low-latency and high-throughput data pipelines.
- Collaboration & Stakeholder Management: Collaborate closely with stakeholders across data engineering, data science, and business teams to align the platform architecture with business needs and evolving technological requirements.
Skills & Qualifications:
Required:
- Bachelors / Masters degree in computer science, Engineering or a related field.
- 10+ years of experience in data architecture, data engineering, or a related field, with a strong background in designing scalable, cloud-based data platforms.
- Extensive experience with AWS services such as S3, Redshift, Glue, Lambda, Kinesis, and RDS, with a deep understanding of cloud architecture patterns.
- Strong proficiency in Databricks, including experience with Apache Spark, Delta Lake, and MLflow for building data pipelines, managing large datasets, and supporting machine learning workflows.
- Expertise in data modelling techniques, including designing star/snowflake schemas, dimensional models, and ensuring data consistency and integrity across the platform.
- Experience with ETL/ELT processes, integrating data from a variety of sources, and optimizing data flows for performance.
- Proficiency in programming languages such as Python and SQL for data manipulation, automation, and data pipeline development.
- Strong knowledge of data governance and security practices, including data privacy regulations (GDPR, CCPA) and tools like AWS IAM, AWS KMS, and AWS CloudTrail.
- Experience with CI/CD pipelines and automation tools for deployment, testing, and monitoring of data architecture and pipelines.
Preferred:
- Experience with real-time streaming data solutions such as Apache Kafka or AWS Kinesis within the Databricks environment.
- Experience with data lake management, particularly using AWS Lake Formation and Databricks Delta Lake for large-scale, efficient data storage and management.
Soft Skills:
- Strong communication skills, with the ability to explain complex technical concepts to business leaders and stakeholders.
- Excellent problem-solving skills with the ability to architect complex, scalable data solutions.
- Leadership abilities with a proven track record of mentoring and guiding data teams.
- Collaborative mindset, capable of working effectively with cross-functional teams, including engineering, data science, and business stakeholders.
- Attention to detail, with a focus on building high-quality, reliable, and scalable data solutions.
Job Classification
Industry: IT Services & ConsultingFunctional Area / Department: Engineering - Software & QARole Category: DBA / Data warehousingRole: Data warehouse Architect / ConsultantEmployement Type: Full timeContact Details:
Company: ZensarLocation(s): Hyderabad+ View Contact
Keyskills: Data Architecture AWS Data Engineering Data Warehousing Aws Glue
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