North American Health care customer is looking to transform the Fertility space. We are looking to support our customer in building digital products for their clinics and customers.
We are on a mission to make a global impact on health care in North America and as we are growing rapidly, we are looking for Product Support Engineer to handle tech requests filed by end-users of a company's product or systems
You are responsible for troubleshooting and resolving product issues and readily suggest improvements, including customer features. You are comfortable developing solutions or pass the problem along to other engineering team members and provide users with progress updates.
We are very much focused on accuracy, attention to detail and timeliness as you seamlessly fit within our sprint process and agile methodology and finally, you’re eager to share your ideas and experiences to help continuously improve as an individual and help your team grow.
Duties and Responsibilities:
- Extract data from multiple sources (Cloud/On-Prem) and ingest it into a data lake (AWS S3) through different AWS Services or APIs or connection protocols such as ODBC, JDBC, etc.
- Cleanse, transform, and maintain data quality in data lakes and data warehouses.
- Build and maintain data lakes, data warehouses, and data marts on AWS as per the business requirements.
- Build data catalogs on AWS Glue.
- Build data pipelines and workflows to ingest raw data and transform/clean data into data lakes and data warehouses respectively using AWS Glue.
- Conduct complex data analysis and report on results.
- Explore ways to enhance data quality and reliability.
- Evaluate business needs and objectives.
- Interpret trends and patterns.
Required Skills and Abilities:
- Previous experience as a data engineer or in a similar role.
- Technical expertise with data models, data scraping, data cleansing, and segmentation techniques.
- Knowledge and understanding of Amazon Web Services such as AWS Glue (Crawler, Job, Database, Workflow), AWS S3, AWS App flow, AWS Athena, AWS Lambda, etc.
- Knowledge and experience in connecting with multiple data sources using different AWS Services or APIs or connection protocols such as ODBC, JDBC, etc.
- Knowledge and experience of Python and PySpark.
- Knowledge and experience in SQL and SparkSQL queries.
- Knowledge of MS Excel and ability to build various views using pivot tables.
- Great numerical, statistical, and analytical skills.
- Data engineering certification will be a plus.
- Knowledge and experience in Beautiful Soup/Selenium/Scrappy will be a plus.
- Knowledge and experience on Terraform will be a plus.
Education and Experience:
- Bachelor’s degree in Computer Science or equivalent required.
- 2+ years of progressive experience in working on AWS services.