Job
Description
ESSENTIAL DUTIES AND RESPONSIBILITIES Work with business users and stakeholders to define and analyze problems and provide optimal technical solutions. Translate business requirements to technical specifications. Involved in design and architecture of the entire scalable data lake architectures using Azure Data Lake (ADLS Gen2), Delta Lake, and Iceberg. Create and maintain design of data ingestion, transformation, and storage strategies for real-time and batch workloads along with orchestration, and semantic layer. Provide solution design for real-time streaming solutions using Confluent Kafka and Flink. Design batch data pipelines using Azure Databricks and Delta Lake. Design data pipeline and data refresh process as per business requirements. Present architecture and solutions to executive-level. Adhere to industry best-practices in all phases of design and architecture of the solution. Provide guidance to ensure data governance, security, and compliance best practices in the architecture. REQUIRED SKILLS & QUALIFICATIONS TECHNICAL SKILLS: Cloud & Data Lake: Azure Data Lake (ADLS Gen2), Databricks, Delta Lake, Iceberg Reporting tools: PowerBI, Tableau or similar toolset Streaming & Messaging: Confluent Kafka, Apache Flink, Azure Event Hubs Big Data Processing: Apache Spark, Databricks, Flink SQL, Delta Live Tables Programming: Python (PySpark, Pandas), SQL Storage & Formats: Parquet, Avro, ORC, JSON Data Modeling: Dimensional modeling, Data Vault, Lakehouse architecture MINIMUM QUALIFICATIONS 8 + years of end-to-end design and architecture of enterprise level data platform and reporting/analytical solutions. 5+ years of expertise in real-time and batch reporting, analytical solution architecture. 4+ years of experience with PowerBI, Tableau or similar technology solutions 3+ years of experience with design and architecture with big data solution. 3+ years of hands-on experience in enterprise level streaming data solution with Python, Kafka/Flink and Iceberg. ADDITIONAL QUALIFICATIONS 8 + years of experience with Dimensional modeling and data lake design methodologies. 8+ years of experience with Relational and Non-relational databases (e.g. SQL Server, Cosmos, etc.) 3 + years of experience with readiness, provisioning, security, and best practices with Azure data platform and orchestration with Data Factory. Experience with working with business stakeholders, requirements & use case analysis. Strong communication and collaboration skills with creative problem-solving skills. PREFERRED QUALIFICATIONS Bachelors degree in computer science or equivalent work experience. Experience with Agile/Scrum methodology. Experience with tax and accounting domain a plus. Azure Data Engineer certification a plus. Applicants may be required to appear onsite at a Wolters Kluwer office as part of the recruitment process.
