Data Lake Architect

We are seeking a highly skilled and experienced Data Lake Architect to join our dynamic team. This role offers the opportunity to shape our data architecture, drive innovation, and contribute to the success of data-driven initiatives.

Responsibilities

• Data Lake Design and Architecture: Develop and implement a robust and scalable data lake architecture.
• Data Modeling: Design and implement effective data models that align with business requirements and ensure optimal performance.
• Data Governance: Establish and enforce data governance policies, including data quality, security, and compliance standards.
• Metadata Management: Implement metadata management strategies to catalog and document data assets within the data lake, ensuring proper data lineage and accessibility.
• Data Integration and Ingestion: Lead the development of data integration processes to ingest data from various sources into the data lake.
• Security and Access Control: Implement robust security measures, including encryption, access controls, and authentication mechanisms.
• Scalability and Performance Optimization: Design and implement strategies to scale the data lake infrastructure and optimize performance based on evolving business needs.
• Collaboration and Stakeholder Management: Collaborate with cross-functional teams, including data engineers, analysts, and business stakeholders.
• Technology Evaluation and Adoption: Evaluate and recommend new tools and technologies to enhance the data lake ecosystem.
• Training and Documentation: Assist in developing training content and provide documentation to support the platform.

Qualifications

• Bachelor's or Master’s degree in Computer Science, or Information Technology.
• 14+ year of proven experience as a Data Engineer with 4+ year as Data Lake Architect.
• In-depth knowledge of data lake architectures, technologies, and best practices.
• Strong expertise in data modeling, data governance, and metadata management.
• Proficiency in programming languages such as Python, PySpark, Scala.
• Experience with cloud-based data lake platforms (e.g., Azure, AWS).
• Hands on experience with (one or more from each line) :
  • Snowflake
  • Apache Airflow | Apache NiFi | Apache Oozie
  • AWS Glue Data Catalog | Azure Purview
  • Apache Sqoop | AWS DataSync | Azure Data Factory
  • Apache Kafka | AWS Kinesis | Azure Event Hubs
• Experience working with version control platform e.g. git
• Experience with JIRA, Confluence