14 feb
Codifin
Tláhuac
Key Responsibilities:
- Design and implement Data Lakehouse architectures that meet business requirements and are scalable, reliable, and secure.
- Gather and document Master Data Management (MDM) requirements, liaising with various business stakeholders to develop MDM strategy & architecture patterns.
- Analyzing the business requirements, design and develop highly efficient highly scalable Data Ingestion processes.
- Design and build modern data pipelines including ETL mappings, being well versed in writing complex SQL queries.
- Develop and maintain data models, data dictionaries, and data flow diagrams.
- Hands-on working with virtualization, performance tuning, optimization,
and scaling solutions from a storage/processing perspective.
- Maintain batch processing jobs and respond to critical production issues communicate well with stakeholders on their proposal recommendations.
- Conduct research focused on identifying emerging technology solutions that reduce costs, increase efficiencies, provide more value, provide more capabilities, reduce risks, and increase security.
- Implement and maintain data security and access controls.
- Support the Lead Data Architect by contributing improvements to the Data Architecture strategy, evolving best-practices, templates and processes.
- Work collaboratively with Solution Architects, Developers, Testers and other Data Analytics team members to understand constraints and opportunities that may shape and influence Data Architecture deliverables.
**Experience**:
- Bachelor's degree in computer science, computer engineering, electrical engineering, systems analysis or a related field of study, or equivalent job experience.
- Significant experience in Data Architecture, with a deep understanding of data models,
standards and tools used across architecture and engineering.
- At least 2 years’ experience designing and implementation Data Lakehouse architectures in Azure or AWS, hands-on experience with Databricks is desirable.
- Experience of transforming traditional Data Warehousing approaches to Big Data based approaches.
- Demonstrated experience using ETL tools such as IICS/ADF/AWS Glue and SSIS using traditional approaches, experience with more modern real time data pipeline solutions is desirable.
- Demonstrated effectiveness in executive presentation and escalation management. - Demonstrated Data modelling and data mapping experience.
- Experience with Data virtualization & catalogue is a desirable
- Experienced with Agile methodologies.
Skills and Attributes:
- Language Fluency: Must possess 100% fluency in English.
- Robust Data Solutions: Ability to manage complex data requirements and develop robust code that ensures data availability, integrity, quality, and security.
- Interpersonal Excellence: Outstanding interpersonal skills, teamwork, and facilitation capabilities to effectively collaborate across diverse teams.
- Effective Communication: Proficient communicator, adept at conveying concepts and ideas, breaking through barriers, and engaging individuals under pressure.
- Stakeholder Management: Skillfully establish credibility with various technical stakeholders, from executives to engineering, operations, security, and quality assurance.
- Goal-Oriented Planning: Capable of aligning short-term and long-term goals, both independently and within the team, integrating strategic objectives seamlessly.
- Effective Leadership: Set clear goals,
prioritize activities, manage risks, and consistently drive projects to completion.
- Technology Neutrality: Unbiased towards technology, vendor, or product preferences; prioritize results over personal choices.
- Resilience: Unwavering commitment to architectural ideals even in the face of opposition
Tipo de puesto: Tiempo completo
Sueldo: $90,000.00 - $100,000.00 al mes
Horario:
- Turno de 10 horas
Lugar de trabajo: remoto híbrido en 06600, Ciudad de México, CDMX
Muestra tus habilidades a la empresa, rellenar el formulario y deja un toque personal en la carta, ayudará el reclutador en la elección del candidato.