Data Model and Structure Definition: 

• Design and develop conceptual, logical, and physical data models for both structured and unstructured data. 

• Collaborate with stakeholders to understand data requirements and translate them into effective data models. 

• Ensure data models are aligned with business goals and effectively support transactional, analytical and operational needs. 

Data Technologies: 

• Design and develop data technology strategy and associated roadmaps. 

• Utilize cloud-native technologies to implement and manage data models. 

• Work with data tools and platforms (e.g., Hadoop, Spark, Kafka) to handle large volumes of data. 

• Optimize data storage, retrieval, and processing in a cloud environment. 

Data Integration and ETL: 

• Design and implement ETL processes to integrate data from various sources into the data lakes 

• Ensure data quality, consistency, and integrity throughout the data lifecycle. 

• Develop and maintain documentation for data models and ETL processes. 

Performance Tuning and Optimization: 

• Analyze and optimize data models to improve performance and scalability. 

• Monitor and troubleshoot data-related issues to ensure optimal system performance. 

• Implement best practices for data management and governance, including defining best practices around ownership, linage, security, and quality. 

Collaboration and Communication: 

• Work closely with engineers, data scientists, and business analysts to deliver data solutions, oftentimes working directly in code alongside them 

• Communicate complex data concepts and solutions to both technical and non-technical stakeholders, including executives and senior leadership 

• Participate in data architecture reviews and provide recommendations for improvements. 

• Partner with senior leadership to ensure strategic plans are being met. 

• Clear roadblocks by building consensus across the organization via a variety of influencing techniques. 

Minimum Requirements 

• Atleast 10 years of related work experience  

• Proficiency in cloud services and tools (e.g., Amazon S3, Azure Data Lake, Google BigQuery). 

• Expert understanding of data modeling, database design, and delta lake concepts. 

• Expert knowledge of data integration and ETL tools (e.g., dbt, Apache NiFi, Talend, Informatica, Azure Data Factory, Prefect). 

• Strong familiarity with big data technologies (e.g., Hadoop, Spark, Kafka, Delta Lake, Iceberg, Arrow, Data Fusion). 

• Strong familiarity with data governance tooling (e.g. Alation, Collibra, BigID, Purview, Monte Carlo) 

• Strong programming skills in languages such as Python, Java, Scala, or Rust. 

• Excellent problem-solving and analytical skills. 

• Strong communication and interpersonal skills. 

• Ability to work collaboratively in a team environment. 

• Project management and organizational skills.