Job Description

The IT organization at Omnissa is looking for a Data Engineer who is excited about redefining, reimagining, and contributing towards building a modern data infrastructure. We believe data engineering is about harnessing the power of data, built on a solid foundation of software engineering, data modeling, devops skills & analytics. At Omnissa, we are committed to helping our people grow professionally. Our talented employees exemplify our shared values and continue to drive our company to new heights.

Job Role and Responsibility

• As a Data Engineer, you will build end-to-end analytical solutions that are highly scalable, performant, secure, and resilient.

• Develop customer-focused data solutions that create meaningful business impact.

• Design solutions with strategic and long-term focus on code quality, reliability, reusability, maintainability and dataops.

• Build efficient and scalable data services.

Required Skills

• Build data solutions on the AWS Cloud - Spark, Python, AWS Data Services (EMR, Lambda, S3).

• Perform data analysis using Python, complex SQLs, and other tools.

• You should have a minimum of 4 years of work experience in the data engineering space.

• Work closely with Product Managers \ Owners to understand the business requirements and convert them into technical stories

• Hands-on development work on all aspects of data analysis, data provisioning, modeling, performance tuning, and optimization.

• Design, implement and operate large-scale, high-volume, high-performance data structures for analytics

• Build scalable data pipelines for both real time and batch using best practices in data modeling, ETL/ELT processes utilizing various technologies such as Spark, Python, Airflow.

• Understanding of any of the data visualizations & reporting tools like Tableau is good to have.

• Perform root cause analysis of issues that hinder the data quality. Work with data source owner to increase quality and accuracy of the source data.

• Understand and influence best practices for observability & dataops.

• Collaborate with engineers to drive best practices in code quality & reusability, data integrity, test design, analysis, validation, and documentation

• Experienced with various patterns of data ingestion, processing, and curation.

• You understand criticality of data quality, security & governance practices and are adept at it.