Offer summary

Qualifications:

3+ years of experience with architecting AWS cloud-based data solutions., 7+ years of experience in Data Engineering for mid-size to large corporations., Extensive Python and SQL skills, with experience in data modeling and building data integration pipelines., Strong analytical and problem-solving skills, with excellent communication abilities..

Key responsabilities:

Design and build AWS data integration pipelines for data extraction into data lakes.

Manage and develop data models to support standardized processing environments.

Provide support for enterprise integrations and develop integration solutions as needed.

Maintain process documentation and partner with architecture leaders to align on cloud adoption strategies.

Job description

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.