Data Engineer On-site (GDL)

NTT DATA; Región Centro; Presencial; MXN 200,000 - 400,000; Jornada completa

Descripción de la vacante

A global IT services company is seeking an experienced Data Engineer to join our team in Guadalajara, Jalisco. The role requires 6-8 years of experience and strong proficiency in SQL and cloud platforms like AWS. You will design and implement data solutions while collaborating with various teams. This position offers an opportunity to work on diverse data projects in a dynamic environment.

Formación

• 6-8 years of experience supporting software engineering, data engineering, or data analytics projects.
• 2+ years of experience leading a team in data-related projects.
• Strong proficiency in SQL and relational databases.

Responsabilidades

• Design tailored data solutions for customer needs.
• Provide thought leadership on appropriate technologies.
• Collaborate across diverse technical stacks.

Conocimientos

SQL

Data engineering

Cloud platforms

Data visualization

Team leadership

Herramientas

Apache Airflow

PostgreSQL

Python

AWS

Descripción del empleo

Req ID:340437

NTT DATA strives to hire exceptional, innovative and passionate individuals who want to grow with us. If you want to be part of an inclusive, adaptable, and forward‑thinking organization, apply now.

We are currently seeking a Data Engineer On‑site (GDL) to join our team in GDL, Jalisco (MX‑JAL), Mexico (MX).

Data Engineer

On‑site position (GDL)

Data Engineers are responsible for designing, building, and maintaining the systems and processes that collect, store, and analyze data. They gather data from various sources and integrate it into a cohesive system. Responsibilities include designing and implementing ETL (Extract, Transform, Load) processes to clean and prepare data for analysis, creating and maintaining databases to store large volumes of data efficiently, building scalable data pipelines to ensure smooth data flow and accessibility, working with data scientists, analysts, and other stakeholders to understand data needs and provide solutions, and continuously monitoring data systems and optimizing them for better performance and scalability.

Key Responsibilities

• Design and implement tailored data solutions to meet customer needs and use cases, spanning from streaming to data lakes, analytics, and beyond within a dynamically evolving technical stack.
• Provide thought leadership by recommending the most appropriate technologies and solutions for a given use case, covering the entire spectrum from the application layer to infrastructure.
• Demonstrate proficiency in coding skills to efficiently move solutions into production while prioritizing performance, security, scalability, and robust data integrations.
• Collaborate seamlessly across diverse technical stacks.
• Develop and deliver detailed presentations to effectively communicate complex technical concepts.
• Generate comprehensive solution documentation, including sequence diagrams, class hierarchies, logical system views, etc.
• Adhere to Agile practices throughout the solution development process.
• Design, build, and deploy databases and data stores to support organizational requirements.
• Ensure data quality, consistency and governance across multiple sources.

Requirements

• 6 - 8 years of experience supporting Software Engineering, Data Engineering, or Data Analytics projects.
• 2+ years of experience leading a team supporting data related projects to develop end‑to‑end technical solutions.
• Strong proficiency in SQL and experience with relational databases (e.g., PostgreSQL, MySQL, SQL Server).
• Experience with data pipeline tools (e.g., Apache Airflow, Luigi, Prefect).
• Proficiency with at least one programming language (Python, Java, or Scala).
• Experience with cloud platforms (AWS, Azure, or GCP) and their data services (e.g., Redshift, BigQuery, Snowflake, Databricks).
• Familiarity with data modeling, warehousing, and schema design.
• Understanding of data governance, privacy, and security best practices.

Preferred Skills

• Demonstrate production experience in core data platforms.
• Exhibit a strong understanding of Data integration technologies.
• Showcase professional written and verbal communication skills to effectively convey complex technical concepts.
• Knowledge of infrastructure‑as‑code tools.
• Experience with streaming technologies (Kafka, Kinesis, etc).
• Exposure to machine learning data pipelines.

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