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Tata Consultancy Services

Posted 25 Aug 2026

AWS Spark Scala - Data Engineer

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Team
TECHNOLOGY
Posted
25 Aug 2026

About the role

Job Description:

TCS Inviting Application For -- AWS Spark Scala - Data Engineer

EXP Range:6-8 Yrs

Location: Bangalore

Desired Competencies (Technical/Behavioral Competency) 

Must-Have** 

•            Strong experience in programming languages such as Python, Java, or Scala for data manipulation and engineering tasks. 

•            Expertise in SQL and NoSQL databases 

•            Hands-on experience with big data technologies like Hadoop, Spark, Kafka, and Hive to handle large-scale data processing and real-time data streams. 

•            In-depth knowledge of data warehousing solutions such as Amazon Redshift, Google BigQuery, and Snowflake for building and managing data warehouses. 

•            Proficiency in designing, developing, and maintaining ETL (Extract, Transform, Load) processes using tools like Apache NiFi, Talend, or Informatica. 

Good-to-Have

•            Familiarity with cloud platforms like AWS, Azure, or Google Cloud for deploying, managing, and scaling data infrastructure and services. 

•            * Strong understanding of data modeling concepts and techniques to create efficient and scalable data models. 

•            Experience with version control systems such as Git for code management and collaboration. 

•            Knowledge of data governance, data quality standards, and data security practices to ensure compliance and protection of sensitive information 

SN 

Responsibility of / Expectations from the Role  

1 

Design, develop, and maintain scalable data pip elines for extracting, transforming, and loading data from various sources to ensure seamless data flow and accessibility. 

2 

Collaborate with cross-functional teams to integrate data from multiple disparate sources, ensuring consistency, accuracy, and reliability of data. 

3 

Optimize data processing workflows and storage solutions for performance, scalability, and cost-efficiency 

4 

Implement data quality checks and validation processes to ensure the accuracy, completeness, and consistency of data throughout the data lifecycle. 

5 

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