Job Description

• Data Architecture and Strategy:
  • Lead the development and implementation of data architecture strategies that align with business objectives.
  • Design and oversee the architecture of enterprise data warehouses, data lakes, and big data platforms.
  • Establish best practices and standards for data modeling, integration, and management.
• Platform Design and Implementation:
  • Architect, design, and implement data warehouse solutions using platforms like Databricks, Redshift, BigQuery, Synapse,  and Snowflake.
  • Develop scalable big data solutions using cloud data technologies and services.
  • Ensure the data architecture supports data quality, security, and governance requirements.

Responsibilities Duties:

• Technology Leadership:
  • Evaluate and recommend data platforms, tools, and technologies that meet the organization’s needs.
  • Lead the selection and implementation of new data technologies and ensure seamless integration with existing systems.
  • Stay current with industry trends and emerging technologies to guide future data strategies.
• Collaboration and Communication:
  • Work closely with stakeholders across the organization, including data engineers, data scientists, and business analysts, to understand data needs and deliver solutions.
  • Collaborate with IT teams to ensure data infrastructure is optimized for performance, scalability, and reliability.
  • Provide leadership and mentorship to data architecture and engineering teams.

Key Skills:

• Data Integration and Management:
  • Design and implement robust ETL processes to integrate data from various sources into the data warehouse and big data platforms.
  • Oversee the management of metadata, master data, and data lineage across systems.
  • Ensure data consistency, accuracy, and availability for business users.
• Performance Optimization:
  • Monitor and optimize the performance of data platforms and processes.
  • Implement strategies for data archiving, backup, and recovery.
  • Address scalability and performance challenges in large-scale data environments.
• Governance and Compliance:
  • Ensure that data architecture and solutions comply with data governance, privacy, and security policies.
  • Implement data governance frameworks and ensure adherence to regulatory requirements.
  • Establish data stewardship programs to maintain data quality and consistency.

Experiance Qualifications:

Experience:

• 15+ years of experience in data architecture, data warehousing, and big data solutions.
• Extensive experience with data warehouse platforms such as Teradata and Oracle.
• Deep understanding and hands-on experience with big data technologies like Hadoop, HDFS, Hive, and Spark.
• Proven track record of designing and implementing large-scale data architectures in complex environments.

Skills:

• Strong expertise in data modeling, data integration (ETL/ELT), and database design.
• Proficiency in SQL, PL/SQL, and performance tuning in Teradata, Oracle, and other databases.
• Familiarity with cloud data platforms and services is a plus (e.g., AWS Redshift, Google BigQuery, Azure Synapse).
• Experience with data governance, security, and compliance best practices.
• Excellent problem-solving, analytical, and critical-thinking skills.
• Strong leadership, communication, and collaboration abilities.

Preferred Qualifications:

• Experience with additional big data and NoSQL technologies (e.g., Cassandra, MongoDB).
• Familiarity with data visualization and BI tools (e.g., Tableau, Power BI).
• Experience with cloud-based data architectures and hybrid data environments.
• Certifications in data architecture, data warehousing, or related areas.

Benefits:

Training, health, insurance, commuting support, lunch service etc.