IC4 – Sr Data Engineer

Objective of the

L

eads the design, development, and optimization of advanced data solutions, ensuring scalability, reliability, and alignment with business

objectives

. This role plays a critical part in defining data architectures, mentoring team members, and driving the adoption of best practices throughout the data engineering lifecycle. With a strong focus on performance, security, and governance,

ensures

that data solutions contribute to a data-driven culture and deliver measurable business value.

Main

• Lead the design and implementation of robust and scalable data pipelines, enabling efficient ingestion, processing, and storage of structured, semi-structured, and unstructured data.

   

• Collaborate with cross-functional teams to gather requirements, define technical solutions, and align data architectures with business needs.

   

• Develop and

  optimize

  data models using industry-standard techniques to support analytics, reporting, and AI-driven solutions.

   

• Implement advanced data processing workflows, including batch,

  microbatch

  , near real-time, and real-time pipelines, to ensure seamless data availability and performance.

   

• Drive the adoption of data governance and privacy strategies, ensuring compliance with security and regulatory requirements throughout the data lifecycle.

   

• Design and

  maintain

  data architectures, contributing to the scalability and reliability of data lakes, warehouses, and real-time streaming platforms.

   

• Develop monitoring processes and data quality metrics to ensure the reliability, integrity, and completeness of data used for decision-making.

   

• Actively contribute to all phases of the data engineering lifecycle, adhering to Agile

  methodologies

  and ensuring

  timely

  delivery of high-quality solutions.

   

• Mentor and guide junior and mid-level engineers, fostering a collaborative and inclusive team environment.

   

• Maintain and document data architectures, processes, and technical workflows to ensure continuity and knowledge sharing.

   

• Lead the integration of APIs and external data sources,

  optimizing

  data flows and ensuring compatibility with existing architectures.

   

• Manage version control and repository practices to

  maintain

  clean, reliable, and maintainable codebases.

   

• Promote an autonomous work culture by encouraging self-management, accountability, and proactive problem-solving among team members.

   

• Serve as a Spin Culture Ambassador to foster and

  maintain

  a positive, inclusive, and dynamic work environment that aligns with the company's values and culture.

   

  Required Knowledge

  and Experienc

  e

   

  • Minimum

    5

    - 6 years of experience

    in

    data engineering or related fields, with proven

    expertise

    in designing and implementing scalable data solutions.

     

  • Advanced t

    echnical

    expertise

    in

    software development life cycle (SDLC) methodologies.

     

     

  • Advanced understanding of design patterns.

     

     

  • Able to work autonomously and provide support to less qualified professionals.

     

     

  • Advanced experience in the use of Python, Java, and data related frameworks.

     

     

  • Advanced knowledge of dimensional data modeling and advanced techniques in this field, including structured, semi-structured, and unstructured data storage (non-SQL), as well as ETL, ELT construction.

     

     

  • Advanced knowledge in file processing:

    CSV, JSON, Parquet,

    Yaml

    , images, and videos.

     

     

  • Advanced knowledge in data processing: batch,

    microbatch

    , near real-time, and real-time.

     

     

  • Advanced understanding and experience to contribute and implement data privacy strategies.

     

     

  • Advanced understanding and experience in implementing and

    maintaining

    robust data governance strategies.

     

     

  • Advanced knowledge in Data Engineering Lifecycle (also known as Data Processing Lifecycle).

     

     

  • Advanced knowledge in processing

    different types

    of internal and external data sources with API management, for

    subsequent

    processing, storage, and analysis.

     

     

  • Advanced knowledge in understanding Architecture: Business, Solutions, Data, etc.

     

     

  • Advanced mastery in version control: Git,

    Github

    , Gitlab.

     

     

  • Advanced in business vision (business domain), to sensitively

    identify

    how data contributes to the business.

     

     

  • Advanced mastery and evidence with projects using the Google Cloud Platform (GCP) Stack for Data.

     

     

  • Advanced mastery and evidence with projects using the Amazon Web Services (AWS) Stack for Data.

     

     

  • Advanced experience in developing and

    optimizing

    SQL and related queries.

     

     

  • Able to

    effectively and exceptionally socialize the design of the data solution

    without supervision.

     

     

  • Advanced experience in Project Management with Agile

    methodology

    (Scrum or Kanban).

     

     

  • Experience in collaborating on projects to achieve OKRs, warning of risks, and providing business value.

     

     

  • Advanced competence in transparently communicating project status

    .

     

    Spin está comprometida con un lugar de trabajo diverso e inclusivo. Somos un empleador que ofrece igualdad de oportunidades y no discrimina por motivos de raza, origen nacional, género, identidad de género, orientación sexual, discapacidad, edad u otra condición legalmente protegida. Si desea solicitar una adaptación, notifique a su Reclutador.