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Open nowPosted 22 hours agoWe saw it 41 min after it went up

IC4 - Sr Data Engineer

Spin Careers24 open roles

Where
México
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Your applicationOpen nowIC4 - Sr Data EngineerSpin Careers · México

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The clock on this job

Early applications get read.

14.0% of postings close within 7 days. Measured by our own scanner across the market. Spin Careers postings stay open a median of 14 days.

Share of postings closed within
  1. 2.3%1 day
  2. 4.7%3 days
  3. 14.0%7 days
  4. 22.5%14 days
  5. 38.3%30 days
  6. 59.0%60 days
This job: posted 22 hours ago

Spin Careers median: 14 days open

The posting

IC4 – Sr Data Engineer

Job Family: Decision Sciences > Sub-family: Data Engineering

Reports to (role): Data Engineering Lead I Sr Lead I Manager

Objective of the Role

Leads 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 Responsibilities

  • 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 Experience

  • Minimum 5–6 years of experience in data engineering or related fields, with proven expertise in designing and implementing scalable data solutions.
  • Advanced technical 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 (NoSQL), 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.

En Spin estamos comprometidos con construir un lugar de trabajo diverso e inclusivo.

Creemos en la igualdad de oportunidades y promovemos un entorno libre de discriminación por motivos de raza, origen nacional, género, identidad de género, orientación sexual, discapacidad, edad o cualquier otra condición legalmente protegida.

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