About us:
Hexaware Technologies is the fastest growing organization today, Hexaware gives you great growth prospects, the opportunity to work along with brilliant minds and a diverse range of high-profile clients, as well as an ideal work-life balance with 37 global offices.
Our digital offerings have helped our clients achieve operational excellence and customer delight by ‘Powering Human-Machine Collaboration.’ We are now on a journey of metamorphosing the experiences of our customer’s customers by leveraging our industry-leading delivery and execution model, built around the strategy - ‘Automate Everything, Cloudify Everything, Transform Customer Experiences.’ We serve customers in Banking, Financial Services, Capital Markets, Healthcare, Insurance, Manufacturing, Retail, Education, Telecom, Hi-tech & Professional Services (Tax, Audit, Accounting, and Legal), Travel, Transportation, and Logistics. Hexaware services customers in over two dozen languages, from every major time zone and every major regulatory zone.
Our goal is to be the first IT services company in the world to have a 50% digital workforce. For more details Visit us at www.Hexaware.com
Position: Data Engineer
Location: Atlanta, GA
Type: FTE
The Data Engineer will play a leading role on the Enterprise Data Services team, responsible for transforming data from disparate systems to provide insights and analytics for business stakeholders. You’ll leverage cloud-based infrastructure to implement technology solutions that are scalable, resilient, and efficient. You will collaborate with Data Engineers, Data Analysts, DBAs, cross-functional teams, and business leaders.
- 2+ years development experience building and maintaining ETL pipelines
- 2+ years of experience working with database technologies and data development such as Python, PLSQL, etc.
- Demonstrated experience with cloud technologies such as AWS for data ingestion, transformations, processing, etc.
- Solid understanding of writing test cases to ensure data quality, reliability and high level of confidence
- Track record of advancing new technologies to improve data quality and reliability
- Continuously improve quality, efficiency, and scalability of data pipelines
- Expert skills working with queries/applications, including performance tuning, utilizing indexes, and materialized views to improve query performance
- Identify necessary business rules for extracting data along with functional or technical risks related to data sources (e.g. data latency, frequency, etc.)
- Develop initial queries for profiling data, validating analysis, testing assumptions, driving data quality assessment specifications, and define a path to deployment
- Familiar with best practices for data ingestion and data design
