Job description 

We are looking forward to hire Azure Data Factory (ADF) Professionals in the following areas :

Experience

4-6 Years

Job Description

Job Description
Must have skills: Azure data factory, Azure data bricks, Python and  Pyspark
4 + years of professional experience with database technologies and ETL tools. 
2+ years of hands-on experience on designing and developing scripts for custom ETL processes and automation in Azure data factory, Azure databricks, Python, Pyspark etc.
Good knowledge of AZURE Cloud platform services stack - Azure Data Factory, Azure SQL Database, AZURE Data Warehouse, Azure databricks, Azure Blob Storage, Azure Data Lake Storage, HD Insight, Cosmos DB, etc.
Hands-on experience on designing and developing scripts for custom ETL processes and automation in Azure data factory, Azure databricks, Python, Pyspark etc.

Required Technical Competencies

Domain/ Industry Knowledge - Working knowledge of customer's business processes and relevant technology platform or product.

Able to analyse current-state and define to-be processes in collaboration with SME and present recommendations with tangible benefits.

Requirement Gathering and Analysis - Working knowledge of requirement management processes and requirement analysis processes, tools & methodologies.

Able to analyse the impact of change requested/ enhancement/ defect fix and identify dependencies or interrelationships among requirements & transition requirements for engagement.

Technology/Product Knowledge - Working knowledge of technology product/platform standards and specifications.

Able to implement code or configure/customize products, analyse various frameworks/tools, review the code & provide inputs in design and architecture adhering to industry standards/ practices in implementation.

Architecture tools and frameworks - Working knowledge of architecture Industry tools & frameworks.

Able to identify pros/ cons of available tools & frameworks in market and use those as per Customer requirement and explore new tools/ framework for implementation.

Architecture concepts and principles - Working knowledge of architectural elements, SDLC, methodologies.

Able to provides architectural design/ documentation at an application or function capability level and implement architectural patterns in solution & engagements and communicates architecture direction to the business.

Analytics Solution Design - Knowledge of statistical & machine learning techniques like classification, linear regression modelling, clustering & decision trees.

Able to identify the cause of errors and their potential solutions.

Tools & Platform Knowledge - Familiar with wide range of mainstream commercial & open-source data science/analytics software tools, their constraints, advantages, disadvantages, and areas of application.

Required Behavioral Competencies

Accountability - Takes responsibility for and ensures accuracy of own work, as well as the work and deadlines of the team.

Collaboration - Shares information within team, participates in team activities, asks questions to understand other points of view.

Agility - Demonstrates readiness for change, asking questions and determining how changes could impact own work.

Customer Focus - Identifies trends and patterns emerging from customer preferences and works towards customizing/ refining existing services to exceed customer needs and expectations.

Communication - Targets communications for the appropriate audience, clearly articulating and presenting his/her position or decision.

Drives Results - Sets realistic stretch goals for self & others to achieve and exceed defined goals/targets.

Resolves Conflict - Displays sensitivity in interactions and strives to understand others’ views and concerns.