Azure Solution Architect
About the company:
Our Client enables enterprises in their digital transformation journey by offering Consulting & Implementation Services related to Data Analytics &Enterprise Performance Management (EPM).
Job Location : Noida
Position – Azure Solution Architect
Notice period- Immediate to 60 days
Experience – 6+
Job Description:
Your Role and Responsibilities
- Able to drive the technology design meetings, propose technology design and architecture
- Experienced in the design and delivery of enterprise level Highly Available solutions
- Work closely with project management teams to successfully monitor progress of implementation
- Collaborate with Pre-sales team on RFP
- Provide detailed specifications for proposed solutions
- Experienced to Migrate applications to cloud
- Experienced to create Data Lake and Data warehouse solutions
- Ability to implement the solution as per technical requirements
- Identity, authentication, security, privacy, and compliance including Active Directory modern Application Architecture (Queue’s, Micro-Services, Containers etc)
Required Technical and Professional Expertise
- Project management and leadership skills are essential.
- 4+ years of experience developing IT and cloud infrastructure (MS Azure, GPC).
- Working knowledge of MS Azure technology stack and related technology (ie. Data Factory, Data Flow, Synapse Analytics, Synapse ML, Gen2 storage, etc.).
- Master's degree in Computer Science or Software Engineering preferred.
- Current understanding of best practices regarding system security measures.
- Experience in software engineering and design architecture.
- Positive outlook in meeting challenges and working to a high level.
- Advanced understanding of business analysis techniques and processes.
- Good to have Azure ML experience
Preferred Technical and Professional Experience
- MS Azure Certification: Fundamentals, Solution Architect, Data Engineer
Team Merito
About Consulting & Implementation Services Data Analytic & EPM
Similar jobs
Mandatory Skills: Azure Data Lake Storage, Azure SQL databases, Azure Synapse, Data Bricks (Pyspark/Spark), Python, SQL, Azure Data Factory.
Good to have: Power BI, Azure IAAS services, Azure Devops, Microsoft Fabric
Ø Very strong understanding on ETL and ELT
Ø Very strong understanding on Lakehouse architecture.
Ø Very strong knowledge in Pyspark and Spark architecture.
Ø Good knowledge in Azure data lake architecture and access controls
Ø Good knowledge in Microsoft Fabric architecture
Ø Good knowledge in Azure SQL databases
Ø Good knowledge in T-SQL
Ø Good knowledge in CI /CD process using Azure devops
Ø Power BI
Responsibilities
- Design and implement Azure BI infrastructure, ensure overall quality of delivered solution
- Develop analytical & reporting tools, promote and drive adoption of developed BI solutions
- Actively participate in BI community
- Establish and enforce technical standards and documentation
- Participate in daily scrums
- Record progress daily in assigned Devops items
Ideal Candidates should have
- 5 + years of experience in a similar senior business intelligence development position
- To be successful in the role you will require a high level of expertise across all facets of the Microsoft BI stack and prior experience in designing and developing well-performing data warehouse solutions
- Demonstrated experience using development tools such as Azure SQL database, Azure Data Factory, Azure Data Lake, Azure Synapse, and Azure DevOps.
- Experience with development methodologies including Agile, DevOps, and CICD patterns
- Strong oral and written communication skills in English
- Ability and willingness to learn quickly and continuously
- Bachelor's Degree in computer science
- Manages the delivery of large, complex Data Science projects using appropriate frameworks and collaborating with stake holders to manage scope and risk. Help the AI/ML Solution
- Analyst to build solution as per customer need on our platform Newgen AI Cloud. Drives profitability and continued success by managing service quality and cost and leading delivery. Proactively support sales through innovative solutions and delivery excellence.
Work location: Gurugram
Key Responsibilities:
1 Collaborate/contribute to all project phases, technical know to design, develop solutions and deploy at customer end.
2 End-to-end implementations i.e. gathering requirements, analysing, designing, coding, deployment to Production
3 Client facing role talking to client on regular basis to get requirement clarification
4. Lead the team
Core Tech Skills: Azure, Cloud Computing, Java/Scala, Python, Design Patterns and fair knowledge of Data Science. Fair Knowledge of Data Lake/DWH
Educational Qualification: Engineering graduate preferably Computer since graduate
Data Warehouse and Analytics solutions that aggregate data across diverse sources and data types
including text, video and audio through to live stream and IoT in an agile project delivery
environment with a focus on DataOps and Data Observability. You will work with Azure SQL
Databases, Synapse Analytics, Azure Data Factory, Azure Datalake Gen2, Azure Databricks, Azure
Machine Learning, Azure Service Bus, Azure Serverless (LogicApps, FunctionApps), Azure Data
Catalogue and Purview among other tools, gaining opportunities to learn some of the most
advanced and innovative techniques in the cloud data space.
You will be building Power BI based analytics solutions to provide actionable insights into customer
data, and to measure operational efficiencies and other key business performance metrics.
You will be involved in the development, build, deployment, and testing of customer solutions, with
responsibility for the design, implementation and documentation of the technical aspects, including
integration to ensure the solution meets customer requirements. You will be working closely with
fellow architects, engineers, analysts, and team leads and project managers to plan, build and roll
out data driven solutions
Expertise:
Proven expertise in developing data solutions with Azure SQL Server and Azure SQL Data Warehouse (now
Synapse Analytics)
Demonstrated expertise of data modelling and data warehouse methodologies and best practices.
Ability to write efficient data pipelines for ETL using Azure Data Factory or equivalent tools.
Integration of data feeds utilising both structured (ex XML/JSON) and flat schemas (ex CSV,TXT,XLSX)
across a wide range of electronic delivery mechanisms (API/SFTP/etc )
Azure DevOps knowledge essential for CI/CD of data ingestion pipelines and integrations.
Experience with object-oriented/object function scripting languages such as Python, Java, JavaScript, C#,
Scala, etc is required.
Expertise in creating technical and Architecture documentation (ex: HLD/LLD) is a must.
Proven ability to rapidly analyse and design solution architecture in client proposals is an added advantage.
Expertise with big data tools: Hadoop, Spark, Kafka, NoSQL databases, stream-processing systems is a plus.
Essential Experience:
5 or more years of hands-on experience in a data architect role with the development of ingestion,
integration, data auditing, reporting, and testing with Azure SQL tech stack.
full data and analytics project lifecycle experience (including costing and cost management of data
solutions) in Azure PaaS environment is essential.
Microsoft Azure and Data Certifications, at least fundamentals, are a must.
Experience using agile development methodologies, version control systems and repositories is a must.
A good, applied understanding of the end-to-end data process development life cycle.
A good working knowledge of data warehouse methodology using Azure SQL.
A good working knowledge of the Azure platform, it’s components, and the ability to leverage it’s
resources to implement solutions is a must.
Experience working in the Public sector or in an organisation servicing Public sector is a must,
Ability to work to demanding deadlines, keep momentum and deal with conflicting priorities in an
environment undergoing a programme of transformational change.
The ability to contribute and adhere to standards, have excellent attention to detail and be strongly driven
by quality.
Desirables:
Experience with AWS or google cloud platforms will be an added advantage.
Experience with Azure ML services will be an added advantage Personal Attributes
Articulated and clear in communications to mixed audiences- in writing, through presentations and one-toone.
Ability to present highly technical concepts and ideas in a business-friendly language.
Ability to effectively prioritise and execute tasks in a high-pressure environment.
Calm and adaptable in the face of ambiguity and in a fast-paced, quick-changing environment
Extensive experience working in a team-oriented, collaborative environment as well as working
independently.
Comfortable with multi project multi-tasking consulting Data Architect lifestyle
Excellent interpersonal skills with teams and building trust with clients
Ability to support and work with cross-functional teams in a dynamic environment.
A passion for achieving business transformation; the ability to energise and excite those you work with
Initiative; the ability to work flexibly in a team, working comfortably without direct supervision.
Job Description - Sr Azure Data Engineer
Roles & Responsibilities:
- Hands-on programming in C# / .Net,
- Develop serverless applications using Azure Function Apps.
- Writing complex SQL Queries, Stored procedures, and Views.
- Creating Data processing pipeline(s).
- Develop / Manage large-scale Data Warehousing and Data processing solutions.
- Provide clean, usable data and recommend data efficiency, quality, and data integrity.
Skills
- Should have working experience on C# /.Net.
- Proficient with writing SQL queries, Stored Procedures, and Views
- Should have worked on Azure Cloud Stack.
- Should have working experience ofin developing serverless code.
- Must have MANDATORILY worked on Azure Data Factory.
Experience
- 4+ years of relevant experience
We are looking for a savvy Data Engineer to join our growing team of analytics experts.
The hire will be responsible for:
- Expanding and optimizing our data and data pipeline architecture
- Optimizing data flow and collection for cross functional teams.
- Will support our software developers, database architects, data analysts and data scientists on data initiatives and will ensure optimal data delivery architecture is consistent throughout ongoing projects.
- Must be self-directed and comfortable supporting the data needs of multiple teams, systems and products.
- Experience with Azure : ADLS, Databricks, Stream Analytics, SQL DW, COSMOS DB, Analysis Services, Azure Functions, Serverless Architecture, ARM Templates
- Experience with relational SQL and NoSQL databases, including Postgres and Cassandra.
- Experience with object-oriented/object function scripting languages: Python, SQL, Scala, Spark-SQL etc.
Nice to have experience with :
- Big data tools: Hadoop, Spark and Kafka
- Data pipeline and workflow management tools: Azkaban, Luigi, Airflow
- Stream-processing systems: Storm
Database : SQL DB
Programming languages : PL/SQL, Spark SQL
Looking for candidates with Data Warehousing experience, strong domain knowledge & experience working as a Technical lead.
The right candidate will be excited by the prospect of optimizing or even re-designing our company's data architecture to support our next generation of products and data initiatives.
- Key Responsibilities : Use cases to support use case analysis E2E, define capabilities, understand the data and model Machine Learning Operations MLOps Azure Machine Learning, Azure Cognitive Services, Azure DevOps, Overall Azure Cloud Experience, Powershell, DSVM, AML Compute / Training Clusters Azure Infrastructure Experience, Python, Big Data Python Scripting 8 Automate ML models deployments, Manage, monitor, troubleshoot machine learning infrastructure and Setup ML Pipe lines
- Technical Experience : Proven skills experience in Azure AI ML solution design and architecture based solution using Azure Cloud capabilities AML / AKS Proven record of embedding advanced analytical models into business processes Collaborate in multi-functional teams to evaluate business activities, and then develop innovative and effective approaches to tackle teams analytics problems and communicate results bitbucket, Nodejs, PowerBI SQL, Python
- Experience in setting up MLOps framework for AI ML team
- 5+ years of experience in a Data Engineer role
- Graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field.
- Experience with big data tools: Hadoop, Spark, Kafka, etc.
- Experience with relational SQL and NoSQL databases such as Cassandra.
- Experience with AWS cloud services: EC2, EMR, Athena
- Experience with object-oriented/object function scripting languages: Python, Java, C++, Scala, etc.
- Advanced SQL knowledge and experience working with relational databases, query authoring (SQL) as well as familiarity with unstructured datasets.
- Deep problem-solving skills to perform root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
REQUIREMENT:
- Previous experience of working in large scale data engineering
- 4+ years of experience working in data engineering and/or backend technologies with cloud experience (any) is mandatory.
- Previous experience of architecting and designing backend for large scale data processing.
- Familiarity and experience of working in different technologies related to data engineering – different database technologies, Hadoop, spark, storm, hive etc.
- Hands-on and have the ability to contribute a key portion of data engineering backend.
- Self-inspired and motivated to drive for exceptional results.
- Familiarity and experience working with different stages of data engineering – data acquisition, data refining, large scale data processing, efficient data storage for business analysis.
- Familiarity and experience working with different DB technologies and how to scale them.
RESPONSIBILITY:
- End to end responsibility to come up with data engineering architecture, design, development and then implementation of it.
- Build data engineering workflow for large scale data processing.
- Discover opportunities in data acquisition.
- Bring industry best practices for data engineering workflow.
- Develop data set processes for data modelling, mining and production.
- Take additional tech responsibilities for driving an initiative to completion
- Recommend ways to improve data reliability, efficiency and quality
- Goes out of their way to reduce complexity.
- Humble and outgoing - engineering cheerleaders.