Data Modeler - Spark

Data Modeler Job Description : You will work as a Data Modeler who is familiar with Cloud-based architectures and DW/BI/Analytics domain knowledge with experience in Databricks or Spark. You will partner closely with the clients to deliver state-of-the-art engineering solutions. You will articulate and communicate with a diverse set of internal and external stakeholders with varying degrees of technical proficiency and deliver critical business and process-related information to mitigate any risks or failures. You will persistently look for opportunities to address customer needs by being a thought partner in every moment of engagement. Responsibilities : - Spearhead the development of conceptual, logical, and physical data models, while implementing data marts/data warehouse/data lake/data lakehouse on Spark-based platforms - Analyse existing models to identify variances/gaps and devise strategies to achieve alignment. - Establish and enforce best practices and standards for data models. - Generate Data Flow diagrams and relevant artifacts to depict data integrations within targeted systems. - Collaborate closely with Data Owners to understand business data requirements and clarify terms and business rules. - Facilitate walkthrough sessions with Data Owners and stakeholders to review and validate data models for accuracy. - Demonstrate strong communication skills and effective engagement with delivery colleagues to ensure successful project outcomes. - Comply with Data Architecture standards and guardrails. - Proactively manage issues, risks, actions, and dependencies, escalating when necessary. Experience : Must have : - Possess a minimum of 5 years of Data Modelling experience in Data Lake/Delta Lakehouse/Data Warehouse on Spark based platforms on Azure/AWS/GCP. - Demonstrate a minimum of 1 year of experience working with/in Databricks. - Mandatory experience of Data Modelling on Delta Lakehouse - Knowledge in handling Spark streaming data over Delta Lakehouse. - Hands-on experience with data modelling tools for performing reverse and forward engineering of as-is and to-be data models, in any of the industry leading data modelling tools such as Erwin/ ER/Studio etc. - Utilize visual notations for expressing data logical and physical models, state transitions, transformations, and versioning. Familiarity with UML, DPMN, ERDs, etc. is ideal. Good to have : - Knowledge of Databricks concepts like Apache Spark API, Delta, Delta Live, feature stores, DBR, job/interactive clusters, notebook management, Repos, MLFlow - Knowledge of orchestration tools like Azure Data Factory, Airflow - Experience in other cloud DWH like Snowflake, Big Query, and Amazon Redshift. - Knowledge of in any Data Governance tool. - Knowledge of Unity Catalog. - Experience in DevOps and CI/CD. (ref:hirist.tech)

Location: bangalore, IN

Posted Date: 1/19/2025