Data Integration Engineer

Collaborate and work in a global data science team to develop scalable and robust data integration infrastructure.
Engage directly with customers and partners to design and develop data requirements based on functional requirements.
Build custom data integration pipelines from existing source systems into cloud platforms such as AWS, Microsoft Azure etc.
Enable data ingestion, pre-processing, custom data wrangling from filesystems, databases, queues and streams to enable rapid prototyping.
Work with customers to develop custom data handlers and connectors as needed.
Perform a variety of data loads data transformations.
Improve database and application performance with fine tuning.
Work with other project teams for data integrations and data lake requirements.
Automate processes for better stability and performance of application. Qualifications/Requirements
BS or MS degree in Computer Science, Engineering, IT.
Minimum 5+ years of professional experience in data engineering, databases and and/or business analytics.
Experience reading and parsing industrial PID and PFD documents.
Solid background and experience in SQL, Python and/or Java/Scala
Minimum 3 years experience in ETL and data pipeline design for heterogenous data such as time series, streams, queues and text.
Familiarity with containers and container services like Docker, Docker registry and Kubernetes.
Knowledge of test-driven development, agile software development methodologies and tools .
Excellent verbal and written communication skills to work in a global team and with customers on a regular basis.