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Engaged Employer

Programming.Com

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3.8

based on 77 Reviews

72 Programming.Com Jobs

Data Engineer (PySpark, SQL, AWS, Databricks)

Programming.com

3.8

based on 77 Reviews

3-8 years

Bangalore / Bengaluru

1 vacancy

Data Engineer (PySpark, SQL, AWS, Databricks)

Programming.Com

posted 2mon ago

Job Role Insights

Flexible timing

Key skills for the job

Data Analytics AWS SQL SAP Business Intelligence Data Processing Data Governance

+ 4 more

Job Description

Job Description: Position: Data Engineer (PySpark, SQL, AWS, Databricks) Location: Bengaluru, Work From Office (WFO) Experience: 3-5 years, 5-8 years Salary Range: Up to 8 LPA, 12-14 LPA Notice Period: Immediate to 15 days Job description: We are looking for a skilled Data Engineer with expertise in PySpark, SQL, AWS, and Databricks. The ideal candidate will be responsible for designing, developing, and maintaining scalable data pipelines and architectures. You will work closely with cross-functional teams to ensure data integrity and optimize data flow for analytics and business intelligence purposes. Key Responsibilities: Design, develop, and manage robust data pipelines using PySpark and SQL. Work with AWS services to implement data solutions. Utilize Databricks for data processing and analytics. Collaborate with data scientists, analysts, and other stakeholders to understand data requirements. Ensure data quality and integrity throughout the data lifecycle. Optimize and maintain existing data architectures. Troubleshoot and resolve data-related issues. Requirements: Proven experience as a Data Engineer or similar role. Strong proficiency in PySpark, SQL, AWS, and Databricks. Experience in building and optimizing big data pipelines and architectures. Solid understanding of data warehousing concepts and ETL processes. Familiarity with data governance and data security best practices. Excellent problem-solving skills and attention to detail. Strong communication and collaboration skills. Technical Skills: PySpark, SQL, AWS, Databricks

Employment Type: Full Time, Permanent

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