Rate – Market RATE
- At least 5 years of consulting or client service delivery experience on Azure
- At least 5 years of experience in developing data ingestion, data processing and analytical pipelines for big data, relational databases, NoSQL and data warehouse solutions
- Extensive experience providing practical direction within the Azure Native and Hadoop - Minimum of 5 years of hands-on experience in Azure and Big Data technologies such as Powershell, C#, Java, Node.js, Python, SQL, ADLS/Blob, Spark/SparkSQL, Hive/MR, Pig, Oozie and streaming technologies such as Kafka, EventHub, NiFI etc.
- Extensive hands-on experience implementing data migration and data processing using Azure services: Networking, Windows/Linux virtual machines, Container, Storage, ELB, AutoScaling, Azure Functions, Serverless Architecture, ARM Templates, Azure SQL DB/DW, Data Factory, Azure Stream Analytics, Azure Analysis Service, HDInsight, Databricks Azure Data Catalog, Cosmo Db, ML Studio, AI/ML, etc.
- Cloud migration methodologies and processes including tools like Azure Data Factory, Event Hub, etc.
- 5+ years of hands on experience in programming languages such as Java, c#, node.js, python, pyspark, spark, SQL, Unix shell/Perl scripting etc.
- Minimum of 5 years of RDBMS experience
- Experience in using Hadoop File Formats and compression techniques- Experience working with Developer tools such as Visual Studio, GitLabs, Jenkins, etc.
- Experience with private and public cloud architectures, pros/cons, and migration considerations.
- Bachelors or higher degree in Computer Science or a related discipline.
- Candidate Must Have Completed The Following Certifications
o MCSA Cloud Platform (Azure) Training & Certification
o MCSE Cloud Platform & Infratsructiure Training & Certification
o MCSD Azure Solutions Architect Training & Certification
- DevOps on an Azure platform
- Experience developing and deploying ETL solutions on Azure
- IoT, event-driven, microservices, containers/Kubernetes in the cloud
- Familiarity with the technology stack available in the industry for metadata management: Data Governance, Data Quality, MDM, Lineage, Data Catalog etc.
- Familiarity with the Technology stack available in the industry for data management, data ingestion, capture, processing and curation: Kafka, StreamSets, Attunity, GoldenGate, Map Reduce, Hadoop, Hive, Hbase, Cassandra, Spark, Flume, Hive, Impala, etc.
- Multi-cloud experience a plus - Azure, AWS, Google Professional Skill Requirements
- Proven ability to build, manage and foster a team-oriented environment
- Proven ability to work creatively and analytically in a problem-solving environment
- Desire to work in an information systems environment
- Excellent communication (written and oral) and interpersonal skills
- Excellent leadership and management skills
- Excellent organizational, multi-tasking, and time-management skills
- Proven ability to work independently