About Gartner:
Gartner, Inc. is the world’s leading research and advisory company and a member of the S&P 500. We equip business leaders with indispensable insights, advice and tools to achieve their mission-critical priorities today and build the successful organizations of tomorrow. Our unmatched combination of expert-led, practitioner-sourced and data-driven research steers clients toward the right decisions on the issues that matter most.
Gartner Recruitment Responsibilities:
- Participate in architecture design and implementation of high-performance, scalable and optimized data solutions.
- Design, build and automate the deployment of data pipelines and applications to support data scientists and researchers with their reporting and data requirements.
- Integrate data from a wide variety of sources, including on premise databases and external data sources with rest APIs and harvesting tools.
- Collaborate with internal business units and data science teams on business requirements, data access, processing/transformation and reporting needs and leverage existing and new tools to provide solutions.
- Effectively support and partner with businesses on implementation, technical issues and training on the datalake ecosystem
- Work with team on managing AWS resources (EMR, ECS clusters, lambda, glue etc.) and continuously improve deployment process of our applications
- Work with administrative resources and support provisioning, monitoring, configuration and maintenance of AWS tools.
- Promote the integration of new cloud technologies and continuously evaluate new tools that will improve the organization’s capabilities while leading to lower total cost of operation.
- Support automation efforts across the data analytics team utilizing Infrastructure as Code (IaC) using Terraform, Configuration Management, and Continuous Integration (CI) / Continuous Delivery (CD) tools such as Jenkins.
- Work with the team to implement data governance, access control and identify and reduce security risks.
Preferred skill:
- Experience working with both structured and unstructured data
- Experience working with Spark, Hive, HDFS, MR, Apache Kafka/AWS Kinesis
- Experience with version control tools (Git, Subversion)
- Experience using automated build systems (CI/CD)
- Experience working in different programming languages (Java, python, scala)
- Experience of Data Structures and algorithms
- Knowledge of different databases technologies (Relational, NoSQL, Graph, Document, Key-Value, Time Series). This should include building and managing scalable data models.
- Knowledge of Cloud based platforms (AWS)
- Knowledge of TDD/BDD
- Strong desire to improve upon their skills in ETL, software development, frameworks and technologies