Sr. Software Engineer - Data Engineering

Key Skills

Apache Hive, Apache Kafka, AWS, AWS Kinesis, Cloud computing, Continuous Integration & Continuous Delivery - CI/CD, Data Governance, Design, ETL frameworks, Git, HDFS, Machine learning techniques, NoSQL, Software Development, Spark Core, SQL

Job Description

About the role

Gartner is looking for a Sr. Software Engineer focusing on data engineering. This person will be a part of team developing and supporting Gartner ‘s client facing experience. This includes supporting all the data related operations within the team. This position will provide an opportunity to work with on several different technologies focusing on data modelling , data services and data science. This includes building and consuming web services, integrating search technologies, and building personalization , recommendation engines, data engineering best practices integration.

What You Will do

• Participate in architecture design and implementation of high-performance, scalable, and optimized data solutions.
• Good Sql understanding with ability to create the data model from scratch.
• Help write and optimize in-application SQL statements.
• Ensure performance, security, and availability of databases.
• Prepare documentations and specifications
• Handle common database procedures such as upgrade, backup, recovery, migration, etc.
• Profile server resource usage, and optimize and tweak as necessary
• 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, 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.

What you will need

• 5-7 years of experience in Solution, Design and Development of Cloud based data models, ETL Pipelines and infrastructure for reporting, analytics, and data science.
• Experience working with both structured and unstructured data.
• Strong proficiency with SQL and its variation among popular databases
• Experience with some of the modern relational databases
• Skilled at optimizing large complicated SQL statements
• Knowledge of best practices when dealing with relational databases
• Capable of configuring popular database engines and orchestrating clusters as necessary
• Ability to plan resource requirements from high level specifications
• Capable of troubleshooting common database issues.
• 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, etc…). This should include building and managing scalable data models.
• Knowledge of ML model deployment
• Knowledge of Cloud based platforms (AWS)
• Knowledge of TDD/BDD
• Strong desire to improve upon their skills in software development, frameworks, and technologies