We are looking for a highly skilled and experienced Data Architect to join our team. The ideal candidate will have a deep understanding of big data technologies and experience working with Hadoop, Python, Snowflake, and Databricks. As a Data Architect, you will be responsible for designing, implementing, and managing complex data architectures that support our business needs and objectives.
Key Responsibilities:
Design and Architecture:
Design scalable and efficient data architecture solutions to meet the businesss current and future data needs.
Lead the development of data models, schemas, and databases that align with business requirements.
Architect and implement solutions on cloud platforms such as AWS, Azure, or GCP.
Develop and maintain data pipelines and ETL processes using Hadoop, Databricks, and other tools.
Oversee data integration and data quality efforts to ensure data consistency and reliability across the organization.
Implement data governance and best practices for data security, privacy, and compliance.
Collaboration and Leadership:
Work closely with data engineers, data scientists, and business stakeholders to understand data requirements and translate them into technical solutions.
Provide technical leadership and mentorship to junior data engineers and architects.
Collaborate with cross-functional teams to ensure data solutions align with business goals.
Optimization and Performance:
Optimize existing data architectures for performance, scalability, and cost-efficiency.
Monitor and troubleshoot data systems to ensure high availability and reliability.
Continuously evaluate and recommend new tools and technologies to improve data architecture.
Qualifications:
Bachelors degree in Computer Science, Information Technology, or a related field. A Masters degree is preferred.
10+ years of experience in data architecture, data engineering, or a related field.
Proven experience with Hadoop ecosystems (HDFS, MapReduce, Hive, HBase).
Strong programming skills in Python for data processing and automation.
Hands-on experience with Snowflake and Databricks for data warehousing and analytics.
Experience with cloud platforms (AWS, Azure, GCP) and their data services.
Familiarity with data modeling tools and methodologies.
Skills:
Deep understanding of big data technologies and distributed computing.
Strong problem-solving skills and the ability to design solutions to complex data challenges.
Excellent communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.
Knowledge of SQL and database performance tuning.
Experience with CI/CD pipelines and automation in data environments.
Preferred Qualifications:
Certification in cloud platforms such as AWS Certified Data Analytics, Google Professional Data Engineer, or Microsoft Certified: Azure Data Engineer Associate.
Experience with additional programming languages like Java or Scala.
Knowledge of machine learning frameworks and their integration with data pipelines