IN Data Engineer - Data Platforms-AWS

Key Responsibilities - Design and develop data pipelines utilizing Amazon Redshift, Snowflake, and DBT to transform raw data into actionable insights. - Collaborate with cross-functional teams to gather requirements and design scalable data solutions that meet business needs. - Implement and manage data integration processes using Azure Data Factory and Apache Airflow to ensure seamless data flow across systems. - Optimize and maintain data warehouses to enhance performance and support analytics teams in data-driven decision-making. - Develop and enforce best practices for data management, ensuring data quality, reliability, and security across all data assets. - Conduct performance tuning and troubleshooting of data pipelines to ensure optimal execution and minimal downtime. - Provide technical guidance and mentorship to junior data engineers and other team members, fostering a collaborative learning environment. - Stay updated with the latest industry trends and technologies to continuously improve and innovate data engineering practices.

Overview - The Data Engineer - AWS role is crucial for designing, implementing, and optimizing data pipelines and architectures within a consulting environment. - Based in Mumbai, the role involves leveraging advanced data warehousing technologies to drive client success. - The engineer will collaborate with cross-functional teams to ensure data solutions are scalable and meet business needs. - This position requires a deep understanding of cloud-based data solutions, particularly within AWS environments, to support data-driven decision-making. - As a Data Engineer, you will be tasked with creating robust data solutions that enhance the client's ability to analyze and utilize data effectively. - You will play a key role in developing data models and implementing data integration processes using state-of-the-art tools. - Working in a consulting capacity, you will provide strategic insights and technical expertise to optimize clients’ data infrastructures. - The position requires a professional who can bridge the gap between business needs and technical solutions, using a combination of Amazon Redshift, Snowflake, and other leading data technologies. - With a focus on innovation and efficiency, you will help shape the data strategy for numerous high-profile clients. - Your expertise will directly contribute to the scalability and performance of data systems, ensuring they align with organizational goals. - As a Level 3 Data Engineer, you will take ownership of complex data engineering projects and mentor junior team members.

Requirements - 3 to 5 years of experience in data engineering, with a strong focus on data warehouse technologies. - Proven expertise in Amazon Redshift, Snowflake, DBT, and Azure Data Factory. - Hands-on experience with Databricks and Apache Airflow for data pipeline management and orchestration. - Strong understanding of data modeling, ETL processes, and data integration concepts. - Excellent problem-solving skills and the ability to work independently in a fast-paced consulting environment. - Effective communication and collaboration skills to work with cross-functional teams and stakeholders. - Experience in performance tuning and optimizing data systems to ensure high availability and scalability.