Senior Data Engineer
Jll · Bengaluru · onsite · Posted 61d ago
Not disclosed5–7 yrsfulltimeSourced from
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About this role
Senior Data Engineer Job Description
About JLL Technologies (JLLT):
Education & Experience:
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 world's buildings while enhancing the productivity and happiness of those who occupy them
- 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
- 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
Education & Experience:
- Bachelor's degree in Computer Science, Data Engineering, or a related field (Master's degree preferred)
- Minimum 5+ years of experience in data engineering or full-stack development, with a focus on cloud-based environments
- 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
- 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
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Skills
automated web servicesDevopsGithubgoogle cloud platformamazon web servicesai technologiesETL ProcessesDatabricksPysparkPythonSQLData WarehousingData GovernanceMicroservicesData ValidationMicrosoft Azure