Corporate Vice President, Sr Data Engineer

Key Responsibilities

• Design and develop enterprise infrastructure and platforms required for data engineering.
• Use AWS Cloud technologies to support data needs for expansion of Machine Learning/Data Science capabilities, applications/mobile apps/systems, BI/analytics, and cross-functional teams.
• Create methods and routines to transition data from on-premise systems to the AWS Cloud.
• Store data in AWS Cloud platform and develop transformational logic based on business rules.
• Create and maintain optimal data pipeline architecture. Test and implement data environments.
• Assemble large, complex data sets to meet functional/non-functional business requirements.
• Build the infrastructure required for optimal ETL/ELT (extraction, transformation, and loading) of data from a wide variety of data sources using SQL and AWS big data technologies.
• Utilize AWS Cloud tools like Amazon Relational Database Service (AWS DMS), AWS Database Migration Service (AWS DMS, AWS Glue, Amazon Simple Storage Service (AWS S3), AWS Lambda triggers & functions, etc.
• In-depth knowledge of databricks.
• Should be able to develop the High level and low level data architecture.
• Develop and debug code in PySpark/Spark/Python. Use SQL and/or Postgres.
• Use Data Pipeline, workflow management, and orchestration service tools.
• Proficient with SQL for data analysis.
• Collaborate with Cloud Data Architects, Data Engineers, DBAs, Analytics & Software Engineers.
• Interact with stakeholders, Product Management, and Design teams to understand requirements and resolve issues.

Qualification & Requirements

• 8+ years as a Cloud Data Engineer, Data Engineer, Data Architect, AWS Engineer, etc.
• 3+ years with Amazon Relational Database Service (RDS), AWS Database Migration Service (AWS DMS), Amazon Simple Storage Service (S3) Data Lake, AWS Lambda, etc. in shared service, hybrid environments.
• Highly scalable Data stores, Data Lake, Data Warehouse, Lakehouse, and unstructured datasets.
• Strong expertise in databricks (spark on databricks) delta lake architecture.
• Proficient in Python, Scala, or SQL for building data pipelines and processing data.
• Data integration, data processing, data streaming, message queuing, and/or ETL/ELT.
• Deep knowledge of cloud platforms (Azure, AWS, or GCP) and experience in managing cloud-based data storage and compute resources.
• Experience with GIT.
• Ability to lead a team of developers.
• Bachelor’s degree in Data Science, Computer Engineering, or related field preferred.

Benefits

We provide a full package of benefits for employees – and have unique offerings for a modern workforce, including leave programs, adoption assistance, and student loan repayment programs. Based on feedback from our employees, we continue to refine and add benefits to our offering, so that you can flourish both inside and outside of work.