Accountable for building small or medium-scale pipelines and data products.
End-to-End solution delivery involving multiple platforms and technologies with small to medium complexity or certain sub-systems of large, complex implementations.
Provides significant input to influence solution architecture.
Build and implement capabilities for continuous integration and continuous delivery aligned with Enterprise DevOps practices.
Accountable for team development and influencing pipeline tool decisions.
Independently review, prepare, design and integrate complex data, correcting problems and recommend data cleansing/quality solutions to issues.
Provide expert documentation and operating guidance for users of all levels.
Rapidly architect, design, prototype/POC, implement, and optimize Cloud/Hybrid architectures.
Research, experiment, and utilize leading big data methodologies (AWS, Hadoop/EMR, Spark, Kafka, Snowflake and Talend) with cloud/on premise hybrid hosting solutions.
Implement, and test data processing pipelines, and data mining/data science algorithms on a variety of hosted settings (AWS, Client technology stacks).

5+ years of data engineering experience
best practices in Distributed systems
Data warehousing solutions
SQL and NoSQL
ETL tools
CICD
Bigdata
Cloud Technologies (AWS/AZURE)
Python/Spark
Data mesh and Data Lake
Data Fabric
Must have Snowflake and IDMC/ Informatica experience
2+ years of developing and operating production workloads in cloud infrastructure
knowledge of agile/iterative methodologies and toolsets
Candidates must be authorized to work in the US without company sponsorship.

Staff Data Engineer

Key skills