Senior Data Engineer

Title: Senior Data Engineer
Location: Las Vegas, NV (3 days onsite)
Duration: 6 Months


Description

As a member of Data Engineering teams, this role will develop the enterprise data platform in Azure cloud. It will entail loading of the raw data from SQL and Mainframe data sources and processing them by developing data transformation pipelines using Azure technologies like Terraform, Data Factory, Data Bricks, Azure Functions, PySpark/Python, SQL etc.

Top Three

Experience in Data, ETL processing, SQL programming, and exposure to Azure cloud
Programming experience using Python or any object oriented language like Java, C# etc.
Ability to learn the Azure tech stack mentioned above and get certified when on the job

Essential Job Duties & Responsibilities

Liberate data from source data sources into the enterprise data lake and operational data stores
Map data from the source systems into curated entities and their functional views
Implement master data management strategies
Design, implement and deploy data pipeline solutions with data lineage capabilities using Azure Data Factory and Databricks.
Manage and publish curated data sets.
Work with the business to manage data quality.
Monitor availability, performance, capacity, continuity, security, and service levels of the enterprise data platform and its services
Provide subject matter expertise to other technical teams leveraging services from the enterprise data platform
Delivering and providing production support for Data Engineering services that meet performance standards and service level agreements.
Participating in continually improving processes and procedures for enhancing the efficiency and effectiveness of Data Engineering services to analytic users.
Participating in leveraging emerging innovations related to Data Engineering and work closely with Enterprise Architecture and other teams to operationalize them
Supporting the Data Engineering department in conducting User Groups and other forums as needed to evangelize and promote the adoption of Data Engineering best practices for accessing and using data sets efficiently, effectively, and securely
Supporting enterprise initiatives in building a culture of data-driven decisions to contribute to operational excellence.
Participating in the development of Data Engineering practices focusing on long-term sustainability, reuse, and technical debt reduction in the domain of data management.
Works with stakeholders including the Executive, Product, Data, and Design teams to assist with data-related technical issues and support their data infrastructure needs.
Publishes dashboards that summarize the utilization of data sets in delivering business value impact

Education And Experience Required

Bachelor’s degree in Computer Science or equivalent education.
Minimum 9 years of experience in information technology systems or data services delivery
4+ years of overall experience in designing and delivering Data Engineering services using programming/scripting languages such as Python, Scala, R, SQL, C#, Java, or U-SQL.
2+ year(s) experience in delivering Data Engineering services using a NoSQL platform such as Cosmos DB, Mongo DB, Hadoop, CouchBase, or HDInsights
Experience in using ETL/ELT, Data Quality Management, Meta Data Management, and Master Data Management platforms is highly preferred
Azure Data Engineer certification strongly Needed.
Experience with Microsoft Azure Data Management Platform is strongly preferred
Familiarity with the financial services and/or life insurance industry is preferred