Data Engineering Specialist

About Enroute:

We love technology, and we enjoy what we do. We are always looking for innovation. We have social awareness and try to improve it daily. We make things happen. You can trust us. Our Enrouters are always up for a challenge. We ask questions, and we love to learn.

We pride ourselves on having great benefits and compensations, a fantastic work environment, flexible schedules, and policies that positively impact the balance of work and life outside of it. We care about who you are in the office and who you are as an individual. We get involved, we like to know our people, we want every Enrouter to become part of a great community of highly driven, responsible, respectful, and above all, happy people. We want you to enjoy working with us.

Requirements

Technical Skills:

• Strong Data Engineering experience, including data modeling, data transformation, and data integration.
• Strong hands-on experience with AWS and cloud-based data solutions.
• Strong knowledge of relational databases and SQL.
• Experience with Python for data processing, querying, validation, and automation.
• Hands-on experience with ETL/ELT processes and data pipelines.
• Experience with data mapping and transformation logic.
• Understanding of system architecture, microservices, distributed systems, and data integration patterns.
• Ability to read and interpret system architecture diagrams and technical specifications.
• Experience with GitHub or other version control systems.
• Understanding of SDLC processes and Agile methodologies (Scrum/Kanban).
• Experience with project management tools such as Jira.
• Familiarity with secure data handling, particularly sensitive financial data and PII.

Business & Communication Skills:

• Ability to work directly with business stakeholders to understand requirements and translate them into technical solutions.
• Strong communication skills and ability to collaborate with both technical and non-technical stakeholders.
• Experience gathering and documenting functional and non-functional requirements.
• Ability to create clear technical documentation, user stories, and acceptance criteria.

Responsibilities:

• Collaborate with business stakeholders to understand business needs and translate them into clear functional and non-functional requirements and technical solutions.
• Design, develop, and maintain data models, data mappings, and transformation logic to enable seamless integration between source and target systems.
• Build, test, and maintain ETL/ELT processes and data pipelines on AWS, ensuring data accuracy, reliability, and timely availability.
• Develop and optimize SQL queries for data analysis, validation, and troubleshooting across relational databases.
• Leverage Python to process, validate, query, and automate data workflows.
• Analyze system architecture diagrams and technical specifications to understand data exchanges across microservices and distributed systems, identifying integration points and potential gaps.
• Create and maintain comprehensive documentation, including data flows, mapping specifications, user stories, and acceptance criteria for technical and non-technical stakeholders.
• Participate in Agile (Scrum/Kanban) development processes, including sprint planning, backlog refinement, and sprint reviews, while tracking activities and deliverables in Jira.
• Manage and maintain code, scripts, and technical documentation using GitHub or other version control systems.
• Ensure the secure handling of sensitive financial data and personally identifiable information (PII), adhering to data governance, privacy, and compliance standards.
• Support testing and User Acceptance Testing (UAT) by defining test scenarios, validating data integrity, and collaborating with development teams to identify and resolve defects.
• Communicate project progress, technical risks, dependencies, and key updates effectively to cross-functional teams and leadership.