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Description:
•Data Pipeline Development: Designing and building scalable, efficient, and reliable data pipelines to extract, transform, and load (ETL) data from various sources into data storage systems, such as data lakes or data warehouses.
•Provide leadership on the migration from Hadoop to Azure and on how we leverage data in multiple portfolios
•Data Modeling: Developing and implementing data models that optimize data storage, retrieval, and analysis, considering factors such as data volume, variety, and velocity.
•Data Integration: Integrating data from different sources, including databases, APIs, streaming platforms, and third-party systems, to ensure data consistency and accuracy.
•Data Transformation and Cleansing: Applying data transformation techniques to clean, preprocess, and enrich data, ensuring its quality and readiness for analysis and reporting.
•Data Warehousing and Storage: Designing and maintaining data warehouses or data lakes to efficiently store and manage large volumes of structured and unstructured data.
•Data Governance and Security: Implementing data governance practices and security measures to protect sensitive data, ensure data privacy, and comply with regulations such as GDPR or CCPA.
•Performance Optimization: Monitoring and optimizing data processing and query performance, identifying and resolving bottlenecks to improve data retrieval and analysis efficiency.
•Collaboration with Data Analysts and Scientists: Collaborating with data analysts and data scientists to understand their requirements and provide them with reliable, accurate, and well-organized data sets for analysis and modeling.
Key Skillsets :
•Strong Programming and Scripting Skills: Proficiency in programming languages such as Python, SQL, or Scala, as well as experience with scripting and automation tools, for data manipulation, ETL processes, and pipeline development.
•Experience with Azure cloud, Azure data bricks, SQL , Spark, Scala or Python
•Experience in Jira, Github, DevOps tools
•Data Integration and ETL Tools: Familiarity with tools and frameworks for data integration and ETL processes, such as Apache Kafka, Apache Spark, Apache Airflow, or Talend.
•Data Modeling and Database Design: Knowledge of data modeling concepts, dimensional modeling, and schema design to create efficient and scalable database structures.
•Big Data Technologies: Experience with big data platforms and technologies like Apache Hadoop, Apache Hive, Apache HBase, or Apache Cassandra for handling large volumes of data.
•Cloud Platforms: Familiarity with cloud platforms and related services for data storage, processing, and analytics.
•Data Governance and Security: Understanding of data governance principles, data security best practices, and compliance requirements to ensure data integrity, privacy, and regulatory compliance.
•Problem-solving and Analytical Thinking: Strong problem-solving skills, attention to detail, and analytical thinking to identify and resolve data-related issues and optimize data pipelines.
•Communication and Collaboration: Excellent communication skills to effectively collaborate with cross-functional teams, including data analysts, data scientists, and stakeholders, and to explain complex technical concepts to non-technical stakeholders.
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