Job
Description
Key Responsibilities: Design and implement scalable, reliable, and high-performance data architectures to support business needs. Develop and maintain real-time data streaming solutions using Kafka and other streaming technologies. Utilize AWS cloud services to build and manage data infrastructure, ensuring security, performance, and cost optimization. Create efficient and optimized data models for structured and unstructured datasets. Develop, optimize, and maintain SQL queries for data processing, analysis, and reporting. Work with cross-functional teams to define data requirements and implement solutions that align with business goals. Implement ETL/ELT pipelines using Python and other relevant tools. Ensure data quality, consistency, and governance across the organization. Troubleshoot and resolve issues related to data pipelines and infrastructure. Required Skills and Qualifications: Experience in Data Engineering and Architecture. Proficiency in Python for data processing and automation. Strong expertise in AWS (S3, Redshift, Glue, Lambda, EMR, etc.) for cloud-based data solutions. Hands-on experience with Kafka for real-time data streaming. Deep understanding of data modeling principles for transactional and analytical workloads. Strong knowledge of SQL for querying and performance optimization. Experience in building and maintaining ETL/ELT pipelines. Familiarity with big data technologies like Spark, Hadoop, or Snowflake is a plus. Strong problem-solving skills and ability to work in a fast-paced environment. Excellent communication and stakeholder management skills EXPERIENCE 12-14 Years SKILLS Primary Skill: Data Engineering Sub Skill(s): Data Engineering Additional Skill(s): Kafka, Python, Data Modeling, ETL, Data Architecture, SQL, Redshift, Pyspark
