Responsibilities
Design, develop, and maintain scalable and efficient cloud-based data infrastructure using SQL and PySpark
Collaborate with cross-functional teams to understand data requirements, identify potential data sources, and define data ingestion architecture
Design and implement efficient data pipeline frameworks, ensuring the smooth flow of data from various sources to data lakes, data warehouses, and analytical platforms
Troubleshoot and resolve issues related to data processing, data quality, and data pipeline performance
Stay updated with emerging technologies, tools, and best practices in cloud data engineering, SQL, and PySpark
Collaborate with data scientists, analysts, and other stakeholders to understand data requirements and deliver data solutions that meet their needs
Document data infrastructure, data pipelines, and ETL processes, ensuring knowledge transfer and smooth handovers
Create complex automated tests and integrate them into testing frameworks
Requirements
Education & Experience
Bachelor's degree in Computer Science, Data Engineering, or a related field (Master's degree preferred)
Minimum 3-5 years of experience in data engineering or full-stack development, with a focus on cloud-based environments
Technical Skills
Strong expertise in managing big data technologies (Python, SQL, PySpark, Spark) with a proven track record of working on large-scale data projects
Strong Databricks experience
Strong database/backend testing with the ability to write complex SQL queries for data validation and integrity
Strong streaming and real-time API/service validation including automation
Experience with automated web services (WSDL) and microservices (REST) using custom scripts and assertions for data validation and data-driven testing
Experience with cloud platforms such as Amazon Web Services (AWS), Microsoft Azure, or Google Cloud Platform (GCP)
Proficiency in object-oriented programming and software design patterns
Experience working in DevOps model, including installing, configuring, and integrating automation scripts on continuous integration tools (CI/CD) and GitHub for real-time test suite execution and troubleshooting
Experience with Unit, Functional, Integration, User Acceptance, System, and Security testing of data pipelines
Strong experience in designing and implementing data pipelines, ETL processes, and workflow automation
Familiarity with data warehousing concepts, dimensional modeling, data governance best practices, and cloud-based data warehousing platforms (e.g., AWS Redshift, Google BigQuery, Snowflake)
Familiarity with cutting-edge AI technologies and demonstrated ability to rapidly learn and adapt to emerging concepts and frameworks
Core Competencies
Strong problem-solving skills and ability to analyze complex data processing issues
Excellent communication and interpersonal skills to collaborate effectively with cross-functional teams
Attention to detail and commitment to delivering high-quality, reliable data solutions
Ability to adapt to evolving technologies and work effectively in a fast-paced, dynamic environment
Location
On-site –Jalisco,MEX
If this job description resonates with you, we encourage you to apply even if you don’t meet all of the requirements. We’re interested in getting to know you and what you bring to the table!
At JLL, we harness the power of artificial intelligence (AI) to efficiently accelerate meaningful connections between candidates and opportunities. Using AI capabilities, we analyze your application for relevant skills, experiences, and qualifications to generate valuable insights about how your unique profile aligns with the specific requirements of the role you're pursuing.
JLL Privacy Notice
Jones Lang LaSalle (JLL), together with its subsidiaries and affiliates, is a leading global provider of real estate and investment management services. We take our responsibility to protect the personal information provided to us seriously. Generally the personal information we collect from you are for the purposes of processing in connection with JLL’s recruitment process. We endeavour to keep your personal information secure with appropriate level of security and keep for as long as we need it for legitimate business or legal reasons. We will then delete it safely and securely.
For more information about how JLL processes your personal data, please view our Candidate Privacy Statement.
For additional details please see our career site pages for each country.
Jones Lang LaSalle (“JLL”) is an Equal Opportunity Employer and is committed to working with and providing reasonable accommodations to individuals with disabilities. If you need a reasonable accommodation because of a disability for any part of the employment process – including the online application and/or overall selection process – you may email us at HRSCLeaves@jll.com. This email is only to request an accommodation. Please direct any other general recruiting inquiries to our Contact Us page > I want to work for JLL.
Jones Lang LaSalle ("JLL") está comprometida a trabajar con personas con discapacidades y proporcionarles accesibilidad. Si necesita un ajuste razonable para cualquier parte del proceso de empleo – incluyendo la candidatura en línea y/o el proceso general de selección – puede enviarnos un correo electrónico a HRSCLeaves@jll.com. Este correo electrónico es solo para solicitar un ajuste razonable. Por favor, dirija cualquier otra consulta general de reclutamiento a nuestra página Contáctanos > Quiero trabajar para JLL.
