Data Architect

Location: [Jersey city or Boston offices]Hybrid

Employment Type: W2,C2C

Client : Randstad Digital

Interview: In-Person Interview Required

Job Description:

Our client is seeking an experienced Data Architect to join their team. The ideal candidate will have extensive hands-on experience with data warehousing and a strong background in various data technologies, particularly Snowflake, Spark, Kafka, ETL processes, and SQL. This is a full-time position that requires in-person interviews, so candidates must provide accurate locations on their profiles.

Responsibilities:

• Data Architecture Design: Design, implement, and optimize data architectures for large-scale data processing, storage, and analysis.
• Data Pipeline Development: Develop and maintain data pipelines using ETL processes to ensure high data quality and availability.
• Snowflake Management: Work extensively with Snowflake to manage and optimize data warehousing solutions.
• Big Data Processing: Utilize Spark for large-scale data processing and analytics.
• Real-time Data Streaming: Implement and manage Kafka for real-time data streaming.
• Collaboration: Collaborate with cross-functional teams to understand data requirements and deliver solutions that meet business needs.
• Data Integrity: Ensure data integrity, security, and privacy standards are maintained.
• Troubleshooting: Troubleshoot and resolve data-related issues and provide support for data infrastructure.
• Continuous Improvement: Continuously improve data architecture and processes through research and integration of new technologies.

Required Skills and Experience:

• Professional Experience: Minimum of 5 years of experience working with data warehousing and real-time data processing technologies.
• Snowflake Expertise: Extensive experience with Snowflake for data warehousing.
• Spark Proficiency: Strong experience using Spark for big data processing.
• Kafka Knowledge: Proven experience with Kafka for real-time data streaming.
• ETL Processes: Deep understanding and practical experience with ETL processes.
• SQL Mastery: Advanced proficiency in SQL for data querying and manipulation.
• Analytical Skills: Strong analytical and problem-solving skills with the ability to troubleshoot complex data issues.
• Communication Skills: Excellent communication skills to collaborate with technical and non-technical stakeholders.

Preferred Qualifications:

• Cloud Platforms: Experience with cloud platforms such as AWS, Azure, or Google Cloud.
• Additional Tools: Familiarity with other data processing and visualization tools.
• Compliance Knowledge: Knowledge of data governance and compliance regulations.