Lead Data Engineer
- Build and maintain secure and compliant production data processing pipelines on Microsoft fabric and azure to ingest, land and transform data to on data product.
- Ensure that data pipelines and data stores are high-performing, efficient, organized, and reliable, given a set of business requirements and constraints.
- Design, implement, monitor, and optimize data platforms to meet the data pipelines needs from functional and non-functional requirements.
- Responsible for data-related implementation tasks that include provisioning data storage services, ingesting streaming, and batch data, transforming data, implementing security requirements, implementing data retention policies, identifying performance bottlenecks, implementing required monitoring and telemetry and accessing external data sources.
- Design and operationalize large scale enterprise data solutions and applications using one or more Azure data and analytics services!
- Implement data solutions that use the following Azure services: Delta.io, Lakehouse, Fabric, Azure Cosmos DB, , Azure Data Factory, Spark, and Azure Blob storage, Microsoft Purview etc.
- Depending on seniority relevant experience in Data Platforms (in Financial Services industry), Azure's PaaS/SaaS offerings (Fabric, Synapse, Purview, ADF, Azure Data Lake Storage etc.)
- Demonstrable experience in a similar role, with a focus on cloud distributed data processing platform for spark, and modern open table concept like delta/iceberg.
- Solid experience with Azure: Synapse Analytics, Data Factory, Data Lake, Databricks, Microsoft Purview, Monitor, SQL Database, SQL Managed Instance, Stream Analytics, Cosmos DB, Storage Services, ADLS, Azure Functions, Log Analytics, Serverless Architecture, ARM Templates.
- Strong proficiency in Spark, SQL, and Python/scala/Java.
- Experience in building Lakehouse architecture using open-source table formats like delta, parquet and tools like jupyter notebook.
- Strong notions of security best practices (e.g., using Azure Key Vault, IAM, RBAC, Monitor etc.).
- Proficient in integrating, transforming, and consolidating data from various structured and unstructured data systems into a structure that is suitable for building analytics solutions.
- Understand the data through exploration, experience with processes related to data retention, validation, visualization, preparation, matching, fragmentation, segmentation, and enhancement.
- Ability to think strategically and operate in day-to-day delivery mode requirement of the role.
- Demonstrates ability to understand business requirements and the implications of those requirements on current and future roadmaps.
- High level understanding of Azure DevOps
- Agile development processes (SCRUM and Kanban)
- Strong communication, presentation, documentation, and interpersonal skills
- Able to self-manage and work independently in a fast-paced environment with dynamic requirements and priorities.
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