Big data spark scala back-end engineer

4 days ago

Erode, India Tata Consultancy Services Full time

I hope you're doing well I came across your profile and was impressed by your extensive experience as an/a (mention role/skill). We have a similar opportunity to join our dynamic team at TCS. Job Title: Scala Back-End Engineer Locations: Bangalore, India Mode: Full Time 8-16 Years Experience About the Role: We are seeking a skilled and passionate Back-End Engineer with a strong background in data engineering to join our growing team. In this role, you will be responsible for designing, developing, and maintaining scalable and reliable data pipelines and back-end systems. You will work with large datasets, leverage cloud technologies, and collaborate with data scientists and other engineers to deliver impactful data-driven solutions. This position is available in both the United States and India. Responsibilities: Design, develop, and maintain data pipelines using Spark, Python, Scala, and Java. Write efficient and optimized SQL queries for data extraction, transformation, and loading (ETL) processes. Work with Data Frames to manipulate and analyse large datasets. Implement data storage and processing solutions using cloud technologies (preferably AWS or GCP). Build and maintain real-time data streaming pipelines using MSK/Kafka. Utilize S3 for data storage and retrieval. Work with data lake technologies like Iceberg. Ensure data quality, integrity, and security. Collaborate with data scientists and other engineers to understand data requirements and deliver solutions. Participate in code reviews and contribute to improving our development processes. Troubleshoot and resolve issues in data pipelines and back-end systems. Qualifications: Bachelor’s degree in computer science or a related field (or equivalent experience). 5+ years of experience in back-end development with a focus on data engineering. Required Skills: Strong proficiency in Spark, Python, Scala, and Java. Expertise in SQL and working with relational databases. Experience with Data Frames for data manipulation and analysis. Experience with cloud technologies (preferably AWS or GCP). Experience with message streaming platforms like MSK/Kafka. Experience with S3 or similar object storage. Experience with data lake technologies like Iceberg. Solid understanding of data warehousing concepts. Excellent communication and collaboration skills. Bonus Points : Experience with data modelling and schema design. Experience with data governance and data quality management. Experience with Dev Ops practices and CI/CD pipelines. Relevant certifications (e.g., AWS Certified Data Engineer, Google Cloud Certified Professional Data Engineer).

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