Job
Description
Who you areA highly skilled Data Engineer specializing in Data Modeling with experience in designing, implementing, and optimizing data structures that support the storage, retrieval and processing of data for large-scale enterprise environments. Having expertise in conceptual, logical, and physical data modeling, along with a deep understanding of ETL processes, data lake architectures, and modern data platforms. Proficient in ERwin, PostgreSQL, Apache Iceberg, Cloudera Data Platform, and Denodo. Possess ability to work with cross-functional teams, data architects, and business stakeholders ensures that data models align with enterprise data strategies and support analytical use cases effectively. What you’ll doAs a Data Engineer – Data Modeling, you will be responsible for: Data Modeling & Architecture Designing and developing conceptual, logical, and physical data models to support data migration from IIAS to Cloudera Data Lake. Creating and optimizing data models for structured, semi-structured, and unstructured data stored in Apache Iceberg tables on Cloudera. Establishing data lineage and metadata management for the new data platform. Implementing Denodo-based data virtualization models to ensure seamless data access across multiple sources. Data Governance & Quality Ensuring data integrity, consistency, and compliance with regulatory standards, including Banking/regulatory guidelines. Implementing Talend Data Quality (DQ) solutions to maintain high data accuracy. Defining and enforcing naming conventions, data definitions, and business rules for structured and semi-structured data. ETL & Data Pipeline Optimization Supporting the migration of ETL workflows from IBM DataStage to PySpark, ensuring models align with the new ingestion framework. Collaborating with data engineers to define schema evolution strategies for Iceberg tables. Ensuring performance optimization for large-scale data processing on Cloudera. Collaboration & Documentation Working closely with business analysts, architects, and developers to translate business requirements into scalable data models. Documenting data dictionary, entity relationships, and mapping specifications for data migration. Supporting reporting and analytics teams (Qlik Sense/Tableau) by providing well-structured data models. Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Experience in Cloudera migration projects in the banking or financial sector. Knowledge of PySpark, Kafka, Airflow, and cloud-native data processing. Experience with Talend DQ for data quality monitoring. Preferred technical and professional experience Experience in Cloudera migration projects in the banking or financial sector. Knowledge of PySpark, Kafka, Airflow, and cloud-native data processing. Experience with Talend DQ for data quality monitoring. Familiarity with graph databases (DGraph Enterprise) for data relationships. Experience with GitLab, Sonatype Nexus, and CheckMarx for CI/CD and security compliance. IBM, Cloudera, or AWS/GCP certifications in Data Engineering or Data Modeling.
