- Analyses current business practices, processes, and procedures as we'll as identifying future business opportunities for leveraging Microsoft Azure Data & Analytics Services.
- Provide technical leadership and thought leadership as a senior member of the Analytics Practice in areas such as data access & ingestion, data processing, data integration, data modeling, database design & implementation, data visualization, and advanced analytics.
- Engage and collaborate with customers to understand business requirements/use cases and translate them into detailed technical specifications.
- Develop best practices including reusable code, libraries, patterns, and consumable frameworks for cloudbased data warehousing and ETL.
- Maintain best practice standards for the development or cloudbased data warehouse solutioning including naming standards.
- Designing and implementing highly performant data pipelines from multiple sources using Apache Spark and/or Azure Databricks
- Integrating the endtoend data pipeline to take data from source systems to target data repositories ensuring the quality and consistency of data is always maintained
- Working with other members of the project team to support delivery of additional project components (API interfaces)
- Evaluating the performance and applicability of multiple tools against customer requirements
- Working within an Agile delivery / DevOps methodology to deliver proof of concept and production implementation in iterative sprints.
- Integrate Databricks with other technologies (Ingestion tools, Visualization tools).
- Proven experience working as a data engineer
- Highly proficient in using the spark framework (python and/or Scala)
- Extensive knowledge of Data Warehousing concepts, strategies, methodologies.
- Direct experience of building data pipelines using Azure Data Factory and Apache Spark (preferably in Databricks).
- Hands on experience designing and delivering solutions using Azure including Azure Storage, Azure SQL Data Warehouse, Azure Data Lake, Azure Cosmos DB, Azure Stream Analytics
- Experience in designing and handson development in cloudbased analytics solutions.
- Expert level understanding on Azure Data Factory, Azure Synapse, Azure SQL, Azure Data Lake, and Azure App Service is required.
- Designing and building of data pipelines using API ingestion and Streaming ingestion methods.
- Knowledge of DevOps processes (including CI/CD) and Infrastructure as code is essential.
- Thorough understanding of Azure Cloud Infrastructure offerings.
- Strong experience in common data warehouse modeling principles including Kimball.
- Working knowledge of Python is desirable
- Experience developing security models.
- Databricks & Azure Big Data Architecture Certification would be plus
Mandatory skill sets
ADE, ADB, ADF
Preferred skill sets
ADE, ADB, ADF
Years of experience required
813 Years
Education qualification
BE, B.Tech, MCA, M.Tech
Required Skills
Data Engineering, Microsoft Azure
Optional Skills
Accepting Feedback, Accepting Feedback, Active Listening, Analytical Thinking, Business Case Development, Business Data Analytics, Business Intelligence and Reporting Tools (BIRT), Business Intelligence Development Studio, Communication, Competitive Advantage, Continuous Process Improvement, Creativity, Data Analysis and Interpretation, Data Architecture, Database Management System (DBMS), Data Collection, Data Pipeline, Data Quality, Data Science, Data Visualization, Embracing Change, Emotional Regulation, Empathy, Inclusion, Industry Trend Analysis
Employment Type: Full Time, Permanent
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