Data Architect - Spark/Hadoop

Role : Cloud Data Architect

Experience : 10+ Years

Employment Type : Full-time

Job Overview :

- Data Architecture Design : Design and implement comprehensive data architectures, including robust data pipelines, data lakes, and data warehouses, primarily on cloud platforms (e.g., AWS, Azure, GCP please specify if a particular cloud is preferred/required).

- Data Modeling : Develop and optimize advanced data models (e.g., star schema, snowflake schema) to effectively support business intelligence and analytics initiatives.

- Big Data Technologies : Leverage expertise in big data technologies such as Hadoop, Spark, and Kafka to process and analyze large-scale datasets efficiently.

- Database Management : Manage and optimize both relational and NoSQL databases for superior performance, scalability, and reliability.

- ETL/ELT Workflow Development : Develop and maintain efficient ETL/ELT workflows using industry-standard tools like Apache NiFi, Talend, or Informatica.

- Data Security & Compliance : Ensure stringent data security and compliance with relevant regulations such as GDPR and CCPA.

- Automation & DevOps : Automate infrastructure deployment through the implementation of CI/CD pipelines and Infrastructure as Code (IaC) tools (e.g., Terraform, CloudFormation).

- Analytics Integration : Collaborate effectively with analytics teams to integrate machine learning frameworks and popular visualization tools (e.g., Tableau, Power BI).

- Technical Leadership : Provide strong technical leadership and mentorship to junior and mid-

level team members, fostering their growth and development.

Required Skills & Qualifications :

- 10+ years of experience working as a Data Architect, with a focus on cloud-based data solutions.

- Proven expertise in designing and implementing data architectures, including data pipelines, data lakes, and data warehouses on cloud platforms.

- Strong experience in data modeling (star schema, snowflake schema).

- Hands-on experience with big data technologies such as Hadoop, Spark, and Kafka.

- Proficiency in managing and optimizing relational and NoSQL databases.

- Demonstrated experience with ETL/ELT tools like Apache NiFi, Talend, or Informatica.

- Solid understanding and implementation experience of data security and compliance regulations (e.g., GDPR, CCPA).

- Experience with CI/CD pipelines and Infrastructure as Code (IaC) tools (e.g., Terraform, CloudFormation).

- Familiarity with machine learning frameworks and data visualization tools (e.g., Tableau, Power BI).

- Excellent analytical and problem-solving skills.

- Strong collaboration, communication, and interpersonal skills, with the ability to translate business requirements into technical solutions.

- Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related field.