Wipro Recruitment 2023

Wipro, a leading global technology company, is seeking talented and experienced individuals to join our team as Data Engineers. As a Data Engineer, you will be responsible for designing, developing, and maintaining data pipelines and infrastructure to enable efficient data processing and analytics. You will work closely with cross-functional teams to gather requirements, implement data solutions, and ensure data integrity and quality. This is an exciting opportunity for individuals with a strong background in data engineering, excellent problem-solving skills, and a passion for leveraging data to drive business insights.

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Responsibilities:

1. Data pipeline development: Design, build, and maintain scalable and efficient data pipelines to extract, transform, and load (ETL) data from various sources. Develop workflows and data integration processes using tools and technologies such as Apache Spark, Hadoop, or cloud-based services. Ensure the reliability, availability, and performance of data pipelines.
2. Data modeling and database management: Design and implement data models, schemas, and database structures to optimize data storage and retrieval. Develop and maintain data warehouses, data lakes, or other data storage systems. Perform data quality checks and implement data governance practices to ensure data accuracy, consistency, and security.
3. Data transformation and analytics: Collaborate with data scientists and analysts to understand data requirements and enable efficient data processing and analytics. Develop data transformation and aggregation processes to support business intelligence, reporting, and advanced analytics. Apply data cleansing, normalization, and enrichment techniques to improve data quality and usability.

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Skills and Qualifications:

1. Data engineering expertise: Strong knowledge of data engineering concepts, practices, and tools. Proficiency in programming languages such as Python, Java, or Scala. Experience with data pipeline frameworks like Apache Spark or Apache Beam. Familiarity with data integration tools and technologies.
2. Database management: Solid understanding of database management systems (DBMS), data modeling, and SQL. Experience with relational databases such as Oracle, MySQL, or PostgreSQL. Familiarity with NoSQL databases, columnar databases, or cloud-based database services.
3. Big data technologies: Hands-on experience with big data technologies and frameworks such as Hadoop, Apache Hive, Apache Kafka, or Apache HBase. Familiarity with cloud-based data services like Amazon Redshift, Google BigQuery, or Microsoft Azure Data Lake.