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JLL Logo JLL · IT - Software Development

Senior Data Engineer

India, Bengaluru · Job Posted February 20, 2026
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Job Description

Senior Data Engineer Job Description; 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

Job Responsibility

  • 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

  • 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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