Data Engineer

Senior Data Engineer -

(No Remote) -- 100% Onsite in NY
What You Will Do:

• Assist in building a world-class Big Data platform which will give us power to process streams of data , as well as, enable machine learning and advanced analytics capabilities. Everything cloud-based for scalability and speed to market.
• Handle large volumes of data and integrate our platform with a range of internal and external systems.
• Understand new tech and how it can be applied to data management.
• Work with an agile team alongside business, testers, architects and project managers.
• Focus on the development of complex logic integrations
• Maintain and evaluate quality of documentation, code, and business logic and non-functional.
• Keep NFRs as priority by maintaining code, supporting, restoring, monitoring and performance for any delivery
• *If you join us as a Senior, you will be a mentor to a team, and will need to bring some previous experience of this.

• Design, implement, and extend core data system that enables reporting and data visualizations
• Manages data integrations within the company's domain technology stack
• Provide runtime and automation solutions that empower developers to migrate and run workloads in the public cloud
• Responsible for maintaining and supporting all data workflows
• Design, implement, enhancement and support of CI/CD frameworks, container solutions, runtime environments, and supporting public cloud infrastructure
• Produce and maintain complex data workflows to meet all the quality requirements of the data management policy
• Design, and documents database architecture
• Responsible for creating and maintaining operational data store
• Responsible for ingestion and extraction of data using MDM tools like Informatica, Amperity, etc.
• Expertise in Data Warehousing and familiarity with cloud offerings for warehouses.
• Creates and maintains diagnoses, alerting, and monitoring code.
• Builds database schemas, tables, procedures, and permissions
• Develops database utilities and automated reporting
• Prepares written materials for the purpose of documenting activities, providing written reference, and/or conveying information
• Full-stack design, development, deployment, and operation of core data stack including data lake, data warehouse, and data pipelines
• Experience building data flow for data acquisition, aggregation, and modelling, using both batch and steaming paradigms
• Experience working public cloud provider (AWS, Google Cloud Platform, Azure)
• Experience building and managing CI/CD pipelines
• Have created and managed Kubernetes clusters in different types of environments
• Familiarity with access controls, secrets management, monitoring, and service discovery in Kubernetes clusters
• Experience working with containerized workflows, applications, and drive container adoption among developers and teams
• Experience building ingestion, ETL data pipelines, especially via code-oriented systems like Spark, Airflow, Luigi, or similar, and with varied data formats
• Experience operating in a secure networking environment (e.g. behind a corporate proxy) is a plus
• Expertise in data engineering languages such as Python, Java, Scala, SQL
• Familiarity with visualizing data with Power BI, Tableau, and similar tools
• Experience creating business requirements documents and/or other application systems related documents