Job Description

KloudPortal Technology Solutions Private limited offers a range of software solutions to clients worldwide. We take pride in creating solutions that are scalable, optimal and effective. Our team of 60+ engineers is diverse and welcoming.

About the position:

This job posting is for Cloud Data Engineering for a mid-Senior level position at client end. The position is for Work from Home.

Experience: 3+ Years

Responsibilities:

Day to day role will include

• Drive business decisions with technical input and lead the team.
• Design, implement, and support an data infrastructure from scratch.
• Manage AWS resources, including EC2, EMR, S3, Glue, Redshift, and MWAA.
• Extract, transform, and load data from various sources using SQL and AWS big data technologies.
• Explore and learn the latest AWS technologies to enhance capabilities and efficiency.
• Collaborate with data scientists and BI engineers to adopt best practices in reporting and analysis.
• Improve ongoing reporting and analysis processes, automating or simplifying self-service support for customers.
• Build data platforms, data pipelines, or data management and governance tools.

BASIC QUALIFICATIONS Data Engineer/ SDE in Data:

• Bachelor's degree in Computer Science, Engineering, or a related field.
• 3+ years of experience in data engineering.
• Strong understanding of AWS technologies, including S3, Redshift, Glue, and EMR.
• Experience with data pipeline tools such as Airflow and Spark.
• Experience with data modeling and data quality best practices.
• Excellent problem-solving and analytical skills.
• Strong communication and teamwork skills.
• Experience in at least one modern scripting or programming language, such as Python, Java, or Scala.
• Strong advanced SQL skill.

PREFERRED QUALIFICATIONS:

• AWS cloud technologies: Redshift, S3, Glue, EMR, Kinesis, Firehose, Lambda, IAM, Airflow.
• Prior experience in Indian Banking segment and/or Fintech is desired.
• Experience with Non-relational databases and data stores.
• Building and operating highly available, distributed data processing systems for large datasets.
• Professional software engineering and best practices for the full software development life cycle.
• Designing, developing, and implementing different types of data warehousing layers.
• Leading the design, implementation, and successful delivery of large-scale, critical, or complex data solutions.
• Building scalable data infrastructure and understanding distributed systems concepts
• SQL, ETL, and data modelling.
• Ensuring the accuracy and availability of data to customers.
• Proficient in at least one scripting or programming language for handling large volume data processing.
• Strong presentation and communications skills.