Data Architect at Convosight · Remote only · 5 - 10 years · ₹10L - ₹35L / yr · Raised funding · Remote only · Posted 14 Jul 2026
About the job
Must-Have Skills
- 5+ years in data architecture / data engineering, with at least 2+ years in an architect or lead capacity
- Strong SQL — advanced query optimization, indexing, partitioning strategies
- Data modeling — dimensional modeling (star/snowflake schema), normalization/denormalization tradeoffs, entity relationship design
- Cloud data platforms — hands-on with AWS (Redshift, S3, Glue), Azure (Synapse, Data Factory), or GCP (BigQuery, Dataflow)
- Big data ecosystems — Spark, Hadoop, or Kafka for large-scale/streaming data
- Data warehousing — Snowflake, Redshift, BigQuery, or Databricks
- ETL/ELT pipeline design — Airflow, dbt, Fivetran, or similar orchestration tools
- Data governance & security — data lineage, access control, compliance (GDPR/SOC2), master data management
Strongly Preferred
- Experience architecting systems supporting ML/AI pipelines (feature stores, vector DBs, real-time inference data flows)
- Programming — Python or Scala for pipeline development
- API/microservices architecture exposure — understanding how data systems integrate with application layers
- Experience with data mesh / data lake house architectures
- Prior experience presenting architecture decisions to leadership/stakeholders

About Convosight
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Example:
We are looking for an experienced Data Architect to design, develop, and manage the organization's enterprise data architecture. The candidate will be responsible for building scalable data platforms, ensuring data quality and governance, and supporting business analytics through modern data solutions.
Experience Required
Mention the minimum years of experience.
Example:
- Minimum 12 years of experience in Data Architecture, Data Engineering, or related fields.
- 5+ years of experience in the Banking/Financial Services domain is preferred.
Educational Qualification
Mention the required degree.
Example:
- BE/BTech in Computer Science, Information Technology, Software Engineering, Electronics & Communication Engineering, or equivalent.
- OR MCA/MTech/MSc in Computer Science, IT, or related disciplines.
- MBA is preferred.
Technical Skills
List the skills the candidate must have.
Example:
- AWS, Azure, or GCP
- Data Warehousing (DWH)
- ETL/ELT
- Database Management
- Data Modeling
- Data Analytics
- Data Lakes
- Data Governance
Key Responsibilities
Convert the points you received into simple action statements.
Example:
- Design and maintain enterprise data architecture.
- Develop data warehouses and data lakes.
- Define data standards and governance policies.
- Ensure data quality and security.
- Design ETL/ELT processes.
- Integrate data from multiple systems.
- Plan and execute data migration projects.
- Review existing data architecture and recommend improvements.
- Provide technical guidance to project teams.
- Evaluate new data technologies and tools.
Preferred Skills
These are not mandatory but are an advantage.
Example:
- Banking domain experience
- Strong analytical and problem-solving skills
- Good communication skills
- Leadership and stakeholder management
- Experience mentoring technical teams
About Us:
The QX Impact was launched with a mission to make A.I accessible and affordable and deliver AI Products/Solutions at scale for the enterprises by bringing the power of Data, AI, and Engineering to drive digital transformation. We believe without insights; businesses will continue to face challenges to better understand their customers and even lose them. Secondly, without insights businesses won't’ be able to deliver differentiated products/services; and finally, without insights, businesses can’t achieve a new level of “Operational Excellence” is crucial to remain competitive, meeting rising customer expectations, expanding markets, and digitalization.
Job Summary:
We are looking for a Senior Data Engineer who is creative, collaborative, and adaptable to join our agile team of data scientists, engineers, and UX developers. The role focuses on building and maintaining robust data pipelines to support advanced analytics, data science, and BI solutions.
As a Senior Data Engineer, you will work with internal and external data, collaborate with data scientists, and contribute to the design, development, and deployment of innovative solutions.
Key Responsibilities:
- Design, develop, test, and maintain optimal data pipeline and ETL architectures.
- Map out data systems and define/design required integrations, ETL, BI, and AI systems/processes.
- Prepare and optimize data for predictive and prescriptive modeling.
- Collaborate with teams to integrate ERP data into the enterprise data lake, ensuring seamless flow and quality.
- Enhance cloud data infrastructure on AWS or Azure for scalability and performance.
- Utilize big data tools and frameworks to optimize data acquisition and preparation.
- Build architectures to move data to/from data lakes and data warehouses for advanced analytics.
- Develop and curate data models for analytics, dashboards, and reports.
- Conduct code reviews, maintain production-level code, and implement testing approaches.
- Monitor, troubleshoot, and resolve data ingestion workflows to maintain reliability and uptime.
- Drive innovation and implement efficient new approaches to data engineering tasks.
Must-Have Skills:
- Bachelor’s degree in Computer Science, Mathematics, Engineering, or a related field.
- 5+ years of experience working with enterprise data platforms, including building and managing data lakes.
- 3–5 years of experience designing and implementing data warehouse solutions.
- Expertise in SQL, including developing stored procedures (SP) and applying advanced data design concepts.
- Proficiency in Spark (Python/Scala) and Spark Streaming for real-time data pipelines.
- Experience with AWS or Azure services (e.g., AWS Glue, Azure Data Factory, Redshift, Snowflake).
- Familiarity with big data tools such as Apache Kafka, Apache Spark, or Flink.
- Hands-on experience with orchestration tools (e.g., Apache Airflow, Prefect).
- Knowledge of CI/CD processes, version control (e.g., Git, Jenkins), and deployment automation.
- Strong problem-solving, communication, and collaboration skills.
Good-to-Have Skills:
- Experience in integrating ERP data into data lakes.
- Experience with traditional ETL tools (e.g., Talend, Pentaho).
Competencies:
- Tech Savvy - Anticipating and adopting innovations in business-building digital and technology applications.
- Self-Development - Actively seeking new ways to grow and be challenged using both formal and informal development channels.
- Action Oriented - Taking on new opportunities and tough challenges with a sense of urgency, high energy, and enthusiasm.
- Customer Focus - Building strong customer relationships and delivering customer-centric solutions.
- Optimize Work Processes - Knowing the most effective and efficient processes to get things done, with a focus on continuous improvement.
Why Join Us?
- Be part of a collaborative and agile team driving cutting-edge AI and data engineering solutions.
- Work on impactful projects that make a difference across industries.
- Opportunities for professional growth and continuous learning.
- Competitive salary and benefits package.
Application Details
Ready to make an impact? Apply today and become part of the QX Impact team!
Solution Architect – AZURE Data Engineering
Job Overview
We are looking for an experienced Solution Architect – Data Engineering with strong expertise in designing data solutions and hands-on experience with Azure, Synapse, PySpark, Data Warehousing, and Data Lakes. The ideal candidate should have strong architectural and data engineering knowledge.
Key Responsibilities
- Design and implement scalable data architecture and solutions.
- Develop and manage Data Warehouse and Data Lake architectures.
- Design data platforms using Medallion Architecture.
- Lead Data Engineering and ETL activities.
- Work with Azure Synapse Analytics for data processing and analytics.
- Develop data solutions using PySpark / Apache Spark.
- Define and implement data validation and data quality processes.
- Collaborate with business, data, and technology teams to deliver effective data solutions.
Required Skills
- Strong experience in Solution Architecture / Data Architecture.
- Strong knowledge of Data Warehouse and Data Lake architecture.
- Good understanding of Medallion Architecture.
- Strong experience in Data Engineering and ETL.
- Hands-on experience with Microsoft Azure and Azure Synapse Analytics.
- Strong knowledge of PySpark / Apache Spark.
- Experience with Data Validation and Data Quality.
- Good communication and stakeholder management skills.
Experience
8+ Years
Data Engineer – Microsoft Fabric
Location: Pune, India
Work Mode: Hybrid
Experience: 6+ Years
Employment Type: Full-time contactor
Compensation: As per market standards, commensurate with experience and expertise
Shift Timings: 2:00 PM – 11:00 PM IST
Notice Period: 0 – 15 days
About the Role
Jade Business Services (JBS) is seeking a Data Engineer – Microsoft Fabric to join our Pune team and work on enterprise-scale data transformation and analytics initiatives.
We are looking for a hands-on Data Engineer with strong experience in Microsoft Fabric, SQL, Python/PySpark and modern data engineering practices. The candidate will be responsible for building scalable data pipelines, implementing Lakehouse and Warehouse solutions, developing data models and supporting governed, reliable and AI-ready data platforms.
The ideal candidate should be comfortable working with architects, engineering teams and client stakeholders to translate business requirements into scalable and production-ready data solutions.
Roles and Responsibilities
- Design and develop data solutions using Microsoft Fabric, including OneLake, Lakehouse, Warehouse and Data Factory pipelines.
- Build and maintain scalable ETL/ELT pipelines for batch and incremental data processing.
- Develop data ingestion and transformation pipelines using Fabric Data Factory, SQL, Python and/or PySpark.
- Implement Medallion Architecture using Bronze, Silver and Gold layers.
- Work with Lakehouse and Fabric Warehouse for enterprise data processing and analytics.
- Develop and maintain data models, tables, views and optimized SQL queries.
- Build and support semantic models for Power BI and analytical workloads.
- Implement data quality, validation, monitoring and error-handling mechanisms.
- Work with metadata, lineage and governance requirements using Microsoft Purview.
- Implement data security, access controls and role-based permissions across data platforms.
- Support Data Product and domain-oriented data architecture principles.
- Follow DataOps practices including CI/CD, deployment, monitoring and production support.
- Troubleshoot pipeline failures, performance issues and data quality problems.
- Optimize data pipelines, queries and storage for performance and cost efficiency.
- Work closely with Data Architects and business stakeholders to understand requirements and implement technical solutions.
- Participate in technical design discussions, code reviews and architecture reviews.
- Maintain technical documentation, data flow diagrams and pipeline documentation.
- Support production deployments, incident resolution and SLA-driven data platform operations.
- Identify opportunities for automation and AI-assisted improvements across data engineering processes.
Qualifications and Skills
- 6+ years of experience in Data Engineering, Data Integration or Data Platform development.
- Strong hands-on experience with Microsoft Fabric.
- Experience with:
- Microsoft Fabric Lakehouse
- Fabric Warehouse
- OneLake
- Fabric Data Factory / Pipelines
- Semantic Models
- Strong understanding of Lakehouse and Medallion Architecture.
- Strong SQL development and query optimization skills.
- Hands-on experience with Python and/or PySpark.
- Experience developing enterprise ETL/ELT and data integration pipelines.
- Experience with batch and incremental data processing.
- Understanding of data modelling concepts including dimensional modelling.
- Knowledge of data quality, metadata, lineage and data governance.
- Working knowledge of Microsoft Purview.
- Understanding of Data Mesh and Data Product concepts.
- Experience with CI/CD, version control, monitoring and DataOps practices.
- Understanding of cloud security, access controls and data privacy.
- Good troubleshooting and problem-solving skills.
- Strong communication skills and ability to work with distributed and client-facing teams.
Preferred Skills
- Microsoft Fabric or Azure Data certifications.
- Experience migrating workloads from Azure Synapse, SQL Server, Databricks or other data platforms to Microsoft Fabric.
- Experience implementing Medallion Architecture on Microsoft Fabric.
- Experience with Power BI and semantic modelling.
- Exposure to AI/ML, Generative AI or Agentic AI use cases on enterprise data platforms.
- Experience working with Data Products or domain-oriented data solutions.
- Experience in Energy & Utilities, Healthcare, Financial Services or Insurance.
- Experience working with US or international enterprise clients.
What We Expect
The ideal candidate should be hands-on first and capable of independently building, troubleshooting and optimizing Fabric data solutions. You should be able to explain the technical decisions behind your implementation and work effectively with architects and engineering teams to deliver production-ready solutions.
Job Description
• Design and Implement Data Solutions: Lead the design, development, and implementation of scalable and secure Azure-
based data platforms, ensuring integration with various data sources and business systems. Deliver at least 2 major
projects every year with a focus on data engineering best practices.
• Optimize Data Pipelines: Build and optimize end-to-end data pipelines using Azure Data Factory, Azure Databricks, and
Azure Synapse, with an emphasis on automating data workflows. Achieve a 20% reduction in pipeline execution times
within the first 6 months.
• Cloud Infrastructure Management: Manage and maintain the Azure data environment, ensuring high availability, disaster
recovery, and cost optimization. Track and improve system uptime to exceed 99.9% reliability.
• Collaborate with Cross-Functional Teams: Partner with data scientists, data analysts, and business stakeholders to translate
business requirements into efficient data solutions. Facilitate at least 3 collaborative sessions per quarter to address key
business use cases.
• Ensure Data Security & Compliance: Implement data security measures, ensuring compliance with industry regulations
(GDPR, HIPAA, etc.) and company policies. Achieve and maintain full compliance in all data environments within the first
quarter of onboarding.
• Continuous Learning & Knowledge Sharing: Stay up-to-date with emerging Azure technologies, and mentor junior
engineers to promote knowledge sharing. Complete 1 Azure certification annually and conduct at least 2 internal
knowledge-sharing sessions per year.
• Sound knowledge of data governance practices, data quality management, and data security principles.
• Play a pivotal role in shaping our organization's data-driven journey, driving innovation through data analytics and insights.
• Optimize data storage, processing and retrieval mechanisms for performance, cost, and scalability using data storage
services (such as Azure Data Lake Storage, Azure SQL Database, etc.), data processing services (such as Azure Data Bricks,
Azure Synapse, etc.) and data visualization (PowerBI, Qlik, etc.) & integration services (Data API builder, logic apps, etc.)
• Monitor and troubleshoot data platform performance, identify and resolve issues, and provide recommendations for
continuous improvement.
• Collaborate with DevOps teams to automate deployment, configuration, and monitoring processes using Azure DevOps,
PowerShell, or other relevant tools.
• Stay up to date with the latest trends and advancements in cloud data services and provide recommendations on adopting
new technologies or features to enhance the data platform.
• Document technical designs, procedures, and guidelines for data platform engineering and operations
Knowledge, Skills & Experience
Job Experience • Bachelor's degree in Computer Science, Engineering, or a related field. Advanced
degree preferred.
• Proven 6-10 years experience in playing platform engineer or admin role
• Experience with big data technologies such as Apache Spark, Hadoop, or similar
frameworks.
• Solid understanding of cloud computing concepts and experience with cloud
infrastructure management and provisioning.
• Solid understanding of network security concepts and technologies (such as
firewalls, VPNs, intrusion detection/prevention systems, etc.) and data security
concepts and technologies (such as access controls, encryption, observability,
privacy laws/regulations, etc.)
• Experience in a Retail setup is preferred.
Required Skills The position will require someone with the following:
• Strategic Planning
Public
• Communication and Collaboration
• Problem Solving Skills A/B testing & experimentation
• SQL, BI tools, and storytelling with data
At Mitratech, we are a team of technocrats focused on building world-class products that simplify operations in the Legal, Risk, Compliance, and HR functions. We are a close-knit, globally dispersed team that thrives in an ecosystem that supports individual excellence and takes pride in its diverse and inclusive work culture centered around great people practices, learning opportunities, and having fun! Our culture is the ideal blend of entrepreneurial spirit and enterprise investment, enabling the chance to move at a rapid pace with some of the most complex, leading-edge technologies available.
For over 35 years, the experts at Mitratech have been focused on solving the complex needs. Today, we serve 20,000 client companies of all sizes globally, representing 30% of the Fortune 500 and over 500,000 users in over 160 countries.
As we continue to grow, we’re always looking for resourceful, enthusiastic, and fresh perspectives. Join our global team and see what makes Mitratech a truly exceptional place to work!
Job Overview
Principal Data Engineer
About Engineering at Mitratech Legal Solutions
Mitratech's engineering organization is a collaborative and dynamic environment where engineers are empowered to drive technical direction and innovation. Our engineers are passionate about delivering high-quality products and solutions that meet the evolving needs of our customers, and we're committed to fostering a culture of continuous learning and growth.
About the Role
Mitratech is a fast-paced and dynamic environment, and this role requires someone who is adaptable, resilient, and able to thrive in a rapidly changing landscape. If you’re a seasoned engineer with a passion for technical leadership, innovation, and collaboration — including building the data foundations that power trusted reporting and agentic AI-driven products — we’d love to hear from you.
What You Will Do
• Drive technical direction for a significant product domain or platform capability, ensuring alignment with business objectives and customer needs
• Design and maintain data pipelines and reporting models that power trusted business metrics and increasingly feed agentic AI systems (e.g., RAG ingestion, embeddings, vector stores, AI agent workflows)
• Use AI-assisted and agentic engineering tools (e.g., Claude Code, Copilot, Cursor, AI agents) as part of your own workflow, and help other engineers adopt agentic development practices effectively
• Reduce systemic complexity by identifying and leading architectural debt remediation, and developing strategies for ongoing technical debt management
• Partner with Product and Engineering leadership to inform multi-quarter roadmap feasibility, and provide technical guidance and oversight to ensure successful implementation
• Elevate engineering craft across multiple teams through RFCs, mentorship, and knowledge sharing, and develop training programs to improve engineering skills and knowledge
• Represent Mitratech’s technical capabilities externally, including speaking at conferences, contributing to open-source projects, and engaging with industry peers and thought leaders
What We Are Looking For
To be successful in this role, you will need:
• 10+ years of experience in software engineering, with a focus on technical leadership and architecture
• Deep understanding of data engineering principles, including data modeling, data warehousing, reporting, and data governance
• Strong technical expertise in SQL, PostgreSQL, ETL/ELT pipelines, BI tools, and analytics platforms
• Practical experience with AI/LLM-adjacent and agentic AI data work — e.g., RAG ingestion pipelines, embedding generation, vector store management, or building/operating AI agent workflows over data — using AI coding assistants (Claude Code, Copilot, Cursor, or similar) as a regular part of the engineering workflow
• Working knowledge of modern cloud platforms such as AWS
• Experience with BI, reporting, dashboards, and customer-facing analytics
• Experience leading cross-functional initiatives with product, engineering, analytics, and business teams
Nice to Have
• Working knowledge of Ruby on Rails and React
• Experience with a semantic or metrics layer (e.g., dbt Semantic Layer, headless BI)
• Understanding of CI/CD, Git-based workflows, and infrastructure-as-code
The Stack Context
• Modern data stack: Fivetran, Airbyte, dbt, Snowflake, GitHub, Terraform, or similar tools
• Application context (nice to have): Ruby on Rails, React, or similar backend/frontend frameworks
• Data modeling: SQL, analytics models, documentation, testing, naming standards, and version control
• Infrastructure: cloud-based data infrastructure, infrastructure-as-code, CI/CD, monitoring, and cloud storage
• Data workflows: ingestion, transformation, orchestration, reporting, deployment, and change management
• Reporting focus: trusted metrics, scalable reporting models, dashboards, exports, and data quality
• AI surface: data pipelines and quality practices supporting AI/LLM and agentic AI use cases (RAG, embeddings, vector stores, AI agents) alongside traditional BI
Why This Role
This role offers a unique opportunity to drive technical direction and innovation at a rapidly growing company, while also mentoring and coaching engineers to improve their craft. As a Principal Data Engineer at Mitratech, you will have the chance to work on complex and challenging problems spanning trusted reporting and agentic AI systems, collaborate with cross-functional teams, and represent the company's technical capabilities externally. If you're looking for a role that offers a mix of technical leadership, data and reporting depth, agentic AI innovation, and collaboration, this could be the perfect fit for you.
We are an equal-opportunity employer that values diversity at all levels. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, national origin, age, sexual orientation, gender identity, disability, or veteran status.
Job Description:
Experience: 10+ Years
Job Summary
We are looking for an experienced Azure Fabric Data Architect to lead the design and implementation of an enterprise data platform on Microsoft Fabric. The role involves architecting scalable data solutions, defining data governance, and enabling AI-driven analytics for a global financial services client.
Key Responsibilities
- Design end-to-end data architecture using Microsoft Fabric.
- Build enterprise Lakehouse, Data Warehouse, and OneLake solutions.
- Define data ingestion, ETL/ELT, governance, security, and performance strategies.
- Lead architecture for AI-powered analytics, AI Agents, and enterprise chatbots using Azure AI services.
- Work with business stakeholders to translate requirements into technical solutions.
- Mentor engineering teams and provide technical leadership.
Required Skills
- Microsoft Fabric (Data Factory, Lakehouse, Data Warehouse, OneLake)
- Azure Data Engineering
- Power BI
- Azure AI Services / Azure OpenAI
- Data Architecture & Data Modeling
- SQL, Python
- Azure DevOps, CI/CD
- Strong stakeholder management and solution design experience
Preferred: Experience in Capital Markets or Financial Services and Microsoft Azure/Fabric certifications.
NOTE: One technical round is mandatory to be taken F2F from office.
Key Responsibilities
- Lead end-to-end data migration initiatives, including assessment, planning, mapping, transformation, validation, and reconciliation.
- Define and implement data governance frameworks, standards, policies, and processes.
- Design and manage data solutions using Microsoft Azure Data Services.
- Lead development of BI dashboards, reports, KPIs, and analytics solutions.
- Work with business and technical stakeholders to understand reporting and data requirements.
- Develop and maintain data models, data pipelines, ETL/ELT processes, and reporting architecture.
- Ensure data quality, consistency, integrity, security, and compliance throughout migration and reporting processes.
- Identify data risks, dependencies, gaps, and migration challenges and drive their resolution.
- Establish data validation and reconciliation mechanisms to ensure migration accuracy.
- Provide technical leadership and guidance to data engineers, BI developers, and other project team members.
- Collaborate with application, cloud, infrastructure, and business teams during project implementation.
- Monitor data migration and BI deliverables against project timelines, quality standards, and business objectives.
- Prepare technical documentation, data dictionaries, mapping documents, governance guidelines, and project reports.
Required Skills & Experience
- 7+ years of experience in data, migration, BI, or related technology roles.
- Strong experience working on software/IT projects and managing data-related workstreams.
- Hands-on experience with Microsoft Azure Data Services.
- Strong understanding of data migration methodologies, ETL/ELT, data transformation, and reconciliation.
- Experience in Data Governance, Data Quality, Master Data, Metadata Management, and Data Security.
- Strong experience with BI reporting and dashboard development.
- Good understanding of SQL and relational databases.
- Experience with Power BI and data visualization is highly desirable.
- Knowledge of Azure services such as Azure Data Factory, Azure Data Lake, Azure Synapse Analytics, Azure SQL Database, or equivalent.
- Strong understanding of data architecture and data lifecycle management.
- Excellent stakeholder management, communication, analytical, and problem-solving skills.
Technical Lead
Job Description
Role Overview
We are seeking a highly skilled Data Engineering Lead with minimum of 5 years of hands-on experience in Azure data engineering, data warehousing, and automation-driven integration. The ideal candidate should be a proven technical lead, capable of driving end-to-end
project delivery and working closely with customer teams. This is a Work from Office / Customer Site role.
Roles and Responsibilities
• Lead the design, development, and delivery of data engineering and automation projects.
• Architect and implement ETL/ELT pipelines using Azure Data Factory.
• Design and manage enterprise data warehouses including dimensional modeling and
schema optimization.
• Manage Azure components including Storage Accounts, Data Lakes, Azure SQL, and Synapse.
• Drive automation initiatives across data ingestion and transformation workflows.
• Collaborate with business and technical stakeholders to translate requirements into scalable solutions.
• Mentor team members and enforce engineering best practices.
• Serve as the technical anchor responsible for ensuring high-quality, on-time delivery.
Skills and Qualification
• Strong hands-on experience with Azure Data Factory, Azure Storage, Azure SQL/Synapse.
• Deep understanding of data warehousing concepts: star/snowflake schemas, fact/dimension modeling.
• Experience with automation-led data engineering solutions.
• Strong troubleshooting, optimization, and analytical skills.
• Excellent communication and stakeholder management abilities.
• Proven experience as a Technical Lead leading teams and delivery.
Must Have
• Min of 5 years of relevant data engineering experience.
• Strong Azure Data Engineering and Data Warehousing expertise.
• Proven Technical Lead experience.
• Ability to work from office and customer site.
• Strong ownership mindset with a focus on quality and delivery excellence.
Dear Candidate,
Greeting from NAM Info Pvt Ltd.
We have a role for Data Engineer position with NAM Info.
This role will be permanent with NAM info and deploy to client
location NEW DELHI~CHENNAI~HYDERABAD~PUNE~KOLKATA.
Work Mode: WORK FROM OFFICE
A decent hike can be provided based on current CTC
Interview Mode: Virtual
Role Descriptions:
Exp Range: 7 - 10 years
City Locations: NEW DELHI~CHENNAI~HYDERABAD~PUNE~KOLKATA
Key Responsibilities*
Role: Data Engineer
Location: ~NEW DELHI~CHENNAI~HYDERABAD~PUNE~KOLKATA
Skills: Digital: Databricks, Azure Data Factory
Experience Required: 8-10
Descriptions:
Good information and sound knowledge in Azure Synapse Analytics Azure Data Factory (ADF)Big Data technologies and data processing frameworks Azure Data Warehouse and associated Azure data platform services Data integration| data modelling| and performance optimization
Desire candidate
- Candidate should have valid PF.
Regards,
NAM Info







