Data Engineer 1
- 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 framework, 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.
Sounds like you? To apply, you need to be:
- Bachelor's degree in Computer Science, Data Engineering, or a related field. (A master's degree is a plus.)
- Minimum of 2 years of experience in data engineering or full-stack development, with a focus on cloud-based environments.
- Strong expertise in SQL and PySpark, with a proven track record of working on large-scale data projects.
- Experience with cloud platforms (any 1) such as Amazon Web Services (AWS), Microsoft Azure, or Google Cloud Platform (GCP).
- Proficiency in designing and implementing data pipelines, ETL processes, and workflow automation.
- Familiarity with data warehousing concepts, dimensional modelling, and data governance best practices.
- 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 a commitment to delivering high-quality, reliable data solutions.
- Ability to adapt to evolving technologies and work effectively in a fast-paced, dynamic environment.
- Experience with managing big data technologies (e.g., Spark, Python, Serverless Stack, API, etc.).
- Familiarity with cloud-based data warehousing platforms (e.g., AWS Redshift, Google BigQuery, Snowflake, etc.).
- Knowledge of data visualization tools (e.g., Tableau, Power BI) for creating meaningful data reports and dashboards is a plus.
Location:On-site –Bengaluru, KA
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!
About JLL –
For over 200 years, JLL (NYSE: JLL), a leading global commercial real estate and investment management company, has helped clients buy, build, occupy, manage and invest in a variety of commercial, industrial, hotel, residential and retail properties. A Fortune 500® company with annual revenue of $20.9 billion and operations in over 80 countries around the world, our more than 103,000 employees bring the power of a global platform combined with local expertise. Driven by our purpose to shape the future of real estate for a better world, we help our clients, people and communities SEE A BRIGHTER WAY. JLL is the brand name, and a registered trademark, of Jones Lang LaSalle Incorporated. For further information, visit jll.com.
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