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We are looking for a skilled Data Engineer to build and maintain scalable data pipelines, manage large datasets, and support analytics initiatives. This role involves working with Big Data technologies like Spark, Scala, SQL/PLSQL, and cloud-ready environments.
Job Responsibility:
Maintain, develop, and design data ingestion and transformation pipelines using Spark and Scala
Process and optimize SQL and PL/SQL queries for large datasets
Integrate and process data from multiple sources for analytics and reporting
Collaborate with BI and Analytics teams to support reporting and dashboard needs
Ensure data quality, performance, and security
Provide innovative solutions to complex business/technical problems
Identify and resolve technical, integration and development issues
Implement best practices, standards and processes to ensure quality of the final product
Responsible for development of features independently
Continuous build, automated testing, and release management
Participate in status meetings and provide regular updates
Requirements:
Expertise in Spark and Scala for large-scale data processing
Proficiency in Python and SQL, including hands-on experience with PL/SQL
Experience in data integration/ETL workflows
Strong knowledge of relational databases such as Oracle and PostgreSQL
Excellent verbal and written communication skills
Result-oriented with strong analytical and problem-solving skills
Ability to work in a fast-paced, agile, and collaborative environment
Nice to have:
Exposure to cloud data services (AWS preferred)
Proficiency in Linux/Unix shell scripting for automation and data operation
Experience working in Agile environments – Scrum and/or SAFe frameworks
Exposure to DevOps culture and practices, including CI/CD and automation
Understanding of software engineering lifecycle – Development, Testing, and Production Support
Experience in production issue handling and transformation support management
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