Tiger Analytics
Cloud Data Architect
Tiger Analytics, Jersey City, New Jersey, United States, 07390
Tiger Analytics is an advanced analytics consulting firm. We are the trusted analytics partner for several Fortune 100 companies, enabling them to generate business value from data. Our consultants bring deep expertise in Data Science, Machine Learning, and AI. Our business value and leadership have been recognized by various market research firms, including Forrester and Gartner. We are one of the highest-rated employers on Glassdoor.
If you are passionate to work on unstructured business problems that can be solved using data, we would like to talk to you.
Mentorship and solution support to client-facing Data Engineers across key accounts
Review data engineer work and proactively establish the adoption of best practices and frameworks that improve productivity and client satisfaction Work with the DevOps, MLE team to onboard and productionize Data Science models at scale. Implement and manage production management processes around data ingestion, transformation, coding utilities, storage, reporting, and other data integration points. Coordinate between onsite and offshore leadership for regular updates
Engage key client stakeholders to
Review and provide the best solutions on the existing or new architecture requirements. Recommend strategies to improve resiliency, security, and optimize costs. Analyse, architect, design, and actively develop analytics frameworks, data lakes, and other cloud-based data solutions. Design and develop scalable data ingestion frameworks to transform a variety of datasets, capture metadata, lineage and implement data quality
Requirements Bachelor’s degree in Computer Science/or any relevant experience in Information systems. 10 years of experience in the IT field with hands-on experience in system administration and automation 3-5 years of strong hands-on experience with AWS(or another cloud) in building a Data and Analytics platform on the cloud. 1+ years of experience with deploying services on Kubernetes on-prem or on-cloud 3-5 years of strong hands-on expertise on Cloud (AWS/Azure/GCP) with strong experience in working with modern data and analytics frameworks, big data, and DevOps techniques, and is proficient with programming languages (like Python, Java, Scala). 1-2 yrs experience with Cloud data warehouse (Redshift, Snowflake, BigQuery) Solid understanding of building Data Lakes on Cloud environments - Data Integration, Data Pipeline, Data compute, ML Models and Storage, etc. Solid knowledge of and experience with Big data and Stream processing frameworks - Spark, Flink, or other Knowledge of delta lake or similar technology Exposure to operationalizing ML models @ scale on Cloud Solid understanding of DevSecOps and cloud security concepts and how to mitigate security risks in the cloud Must understand the Scrum Agile methodology and have worked on a Scrum team. Knowledge of SQL, non-relational (NoSQL) databases, and Object Stores Good experience working on an onsite/offshore model Knowledge of networking, firewalls, load balancers, etc. AWS Professional Architect Certification is preferred Exceptional communication skills and the ability to communicate appropriately with executives and technical teams. Benefits Significant career development opportunities exist as the company grows. The position offers a unique opportunity to be part of a small, fast-growing, challenging and entrepreneurial environment, with a high degree of individual responsibility.
Review data engineer work and proactively establish the adoption of best practices and frameworks that improve productivity and client satisfaction Work with the DevOps, MLE team to onboard and productionize Data Science models at scale. Implement and manage production management processes around data ingestion, transformation, coding utilities, storage, reporting, and other data integration points. Coordinate between onsite and offshore leadership for regular updates
Engage key client stakeholders to
Review and provide the best solutions on the existing or new architecture requirements. Recommend strategies to improve resiliency, security, and optimize costs. Analyse, architect, design, and actively develop analytics frameworks, data lakes, and other cloud-based data solutions. Design and develop scalable data ingestion frameworks to transform a variety of datasets, capture metadata, lineage and implement data quality
Requirements Bachelor’s degree in Computer Science/or any relevant experience in Information systems. 10 years of experience in the IT field with hands-on experience in system administration and automation 3-5 years of strong hands-on experience with AWS(or another cloud) in building a Data and Analytics platform on the cloud. 1+ years of experience with deploying services on Kubernetes on-prem or on-cloud 3-5 years of strong hands-on expertise on Cloud (AWS/Azure/GCP) with strong experience in working with modern data and analytics frameworks, big data, and DevOps techniques, and is proficient with programming languages (like Python, Java, Scala). 1-2 yrs experience with Cloud data warehouse (Redshift, Snowflake, BigQuery) Solid understanding of building Data Lakes on Cloud environments - Data Integration, Data Pipeline, Data compute, ML Models and Storage, etc. Solid knowledge of and experience with Big data and Stream processing frameworks - Spark, Flink, or other Knowledge of delta lake or similar technology Exposure to operationalizing ML models @ scale on Cloud Solid understanding of DevSecOps and cloud security concepts and how to mitigate security risks in the cloud Must understand the Scrum Agile methodology and have worked on a Scrum team. Knowledge of SQL, non-relational (NoSQL) databases, and Object Stores Good experience working on an onsite/offshore model Knowledge of networking, firewalls, load balancers, etc. AWS Professional Architect Certification is preferred Exceptional communication skills and the ability to communicate appropriately with executives and technical teams. Benefits Significant career development opportunities exist as the company grows. The position offers a unique opportunity to be part of a small, fast-growing, challenging and entrepreneurial environment, with a high degree of individual responsibility.