Senior Data Architect

7 days ago

Pune, India AGILE TECHNOLOGY SOLUTIONS Full time

Job Description :Key Responsibilities :- Design and implement robust, scalable, and optimized data architectures leveraging the Databricks platform and Snowflake ecosystem. - Architect data pipelines and frameworks that are efficient, fault-tolerant, and capable of handling large-scale, complex data processing. - Define data modeling standards, data lakehouse architecture, and best practices for structured and unstructured data management. - Collaborate with enterprise architects to align data platform strategy with overall organizational goals. - Evaluate new technologies, frameworks, and tools to enhance scalability, reliability, and performance. - Develop and manage end-to-end ETL/ELT pipelines using Databricks notebooks, Delta Lake, Snowflake, and Azure Data Factory (ADF). - Ensure seamless integration across diverse data sources on-premises and cloud-based. - Implement efficient data transformation, ingestion, and cleansing frameworks for analytics and AI workloads. - Standardize data pipeline templates for reusability and consistency across teams. - Work extensively with Azure, AWS, or GCP platforms to integrate Databricks and Snowflake with storage layers such as ADLS, Amazon S3, and Google Cloud Storage. - Architect hybrid data solutions enabling smooth data exchange across cloud, on-premise, and third-party applications. - Collaborate with cloud engineering teams to define networking, storage, and compute strategies supporting large-scale data workloads. - Optimize performance of data workflows and clusters by fine-tuning Databricks configurations, SQL queries, caching, and partitioning strategies. - Identify and resolve performance bottlenecks in data ingestion and transformation processes. - Implement monitoring tools and alerts to proactively detect and address performance issues.- Define and enforce data governance frameworks, ensuring compliance with organizational and regulatory standards. - Implement role-based access control (RBAC), encryption, and data masking techniques for sensitive datasets. - Establish data lineage, metadata management, and auditing mechanisms for transparency and traceability. - Ensure compliance with GDPR, HIPAA, and other data protection standards as applicable. - Automate data pipeline deployments using CI/CD tools such as Azure DevOps, Jenkins, or GitHub Actions. - Create monitoring dashboards to track data pipeline performance, latency, and data quality metrics. - Collaborate closely with data scientists, analysts, and business stakeholders to translate analytical requirements into technical deliverables. - Work with product and engineering teams to ensure seamless integration of data solutions with enterprise systems. - Lead and mentor data engineering teams, conduct technical reviews, and ensure adherence to architectural best practices.- Stay current with the latest Databricks, Snowflake, and Azure Data Services advancements. - Evaluate emerging trends in data lakehouse, AI/ML integration, and automation tools. - Drive initiatives to modernize legacy systems and adopt next-generation data architectures (e.g., medallion architecture, data mesh). (ref:hirist.tech)

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