Data Engineer

Position: Data Engineer
Location: 100% Remote
Duration: 6+ Months
Experience: - 8+ Years

Technologies We Use:
AWS Serverless Services Stack (S3, Athena, Lambda, SQS, SNS, Step Functions, Redshift, Glue, etc.),
Python
SQL
Bitbucket/Github
MSSQL Server
Salesforce.

Your Role:

• Execute on a shared technical architectural direction, long-term vision, and guiding principles for data and platforms and ensure alignment with the enterprise technology strategy.
• Design, build out and modify AWS data integration pipelines to modernize and harden process models for extracting data from operational platforms into data lake.
• Build and manage data models (relational, dimensional & NoSQL) to support standardized processing environment. Build deep understanding of how dozens of data sources can be combined for 360-view.
• Provide support for and own enterprise integrations (i.e. Salesforce, AWS Cognito, Enterprise APIs, Google Analytics, Ecommerce, etc.)
• Develop integration solutions in the incubation phase and build prototypes as necessary to validate architecture approaches.
• Develop and maintain SQL queries to support aggregations used for reporting and marketing automation.
• Maintain high standards of process documentation. Provide non-functional requirements according to which the solution is defined, managed, and delivered.
• Partner with architecture and engineering leaders to drive alignment on the right balance between consistency and flexibility in our cloud adoption approach.
• Mentor, educate and train colleagues as requested.

Qualifications
Required Experience:

• 3+ years of experience with architecting and engineering AWS cloud-based Data solutions.
• 7+ years of experience in Data Engineering for mid-size to large corporations.
• Experience supporting and working with data platforms.
• Extensive Python/C coding experience in application to data processing.
• Excellent SQL skills.
• Experience in data modeling (relational, dimensional & NoSQL)
• Experience in building data integration pipelines for transitional and analytical applications
• Experience with cloud-native data and parallel data processing architectures (Data Lake architectures, MPP database engines, serverless data processing pipelines, Spark, etc.)
• Experience consuming data from various sources (databases, file sources, REST services, SOAP services, web-scraping, etc.) and various formats (csv, tsv, json, xml, html, unstructured text, etc.) in Python or C
• Execution of DevOps methodologies and Continuous Integration/Continuous Delivery (CI/CD)
• Experience with Agile (SCRUM, Kanban, etc.) or lean development and able to discuss workflows for different software development processes.
• Attention to detail and results oriented, with a strong product and customer focus.
• Strong analytical and problem-solving skills.
• The ability to work in a team environment.
• Excellent verbal and written communication skills with the ability to talk to technical and non-technical people, including executive management.
• Drive to learn and keep pace with the latest advances in the field; rapidly grasp new technologies to support the environment and contribute to project deliverables.
  
  What We Look For:

• Experience with products in cloud deployment.
• Experience building and implementing scalable applications that use modern design patterns that leverage Cloud platforms.
• Leveraging domain driven design principles to support legacy re-platforming efforts.
• Designing message-based interaction models to support distributed data across the enterprise.
• Excellent problem-solving skills.
• Strong development skills - must be able to work "hands-on."
• Strong team player who enjoys working in a fast-paced atmosphere
• Ability to manage multiple priorities, commitments and projects and organize effectively.
• Self-motivated and passionate about what you do.
• Strong written and verbal communication skills.