Senior Data Engineer Job Description
About JLL Technologies (JLLT):
JLL Technologies is a specialized group within JLL that delivers unparalleled digital advisory, implementation, and services solutions to organizations globally
We provide best-in-class technologies to bring digital ambitions to life by aligning technology, people, and processes
Our goal is to leverage technology to increase the value and liquidity of the worlds buildings while enhancing the productivity and happiness of those who occupy them
What the Job Involves:
We are seeking a Senior Data Engineer who is a self-starter to work in a diverse and fast-paced environment as part of our Enterprise Data team
This individual contributor role is responsible for designing and developing data solutions that are strategic to the business and built on the latest technologies and patterns
This is a global role that requires partnering with the broader JLLT team at the country, regional, and global levels by utilizing in-depth knowledge of data, infrastructure, technologies, and data engineering experience
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:
Bachelors degree in Computer Science, Data Engineering, or a related field (Masters degree preferred)
Minimum 5+ years of experience in data engineering or full-stack development, with a focus on cloud-based environments
Technical Skills:
Advanced 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
Advanced 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
