Senior Data Engineer - AWS, Java

Yesterday

Apply Now

Receive Emails with Similar Jobs

Rearc

WebsiteLinkedInAll Job Openings

Accelerate Your Cloud Development Efforts

Cloud Computing • DevOps • Software Development • IT Transformation

51 - 200

Description

• Provide strategic vision and technical leadership in data engineering, guiding the development and execution of advanced data strategies that align with business objectives. • Design and architect complex data pipelines and scalable architectures, leveraging advanced tools and frameworks (e.g., Apache Kafka, Kubernetes) to ensure optimal performance and reliability. • Lead the exploration and adoption of new technologies and methodologies in data engineering, driving innovation and continuous improvement across data processes. • Apply deep expertise in ETL processes, data modelling, and data warehousing to optimize data workflows and ensure data integrity and quality. • Collaborate closely with cross-functional teams to understand requirements and deliver impactful data solutions—mentor and coach junior team members, fostering their growth and development in data engineering practices. • Contribute to thought leadership in the data engineering domain through technical articles, conference presentations, and participation in industry forums.

Requirements

• 8+ years of experience in data engineering, showcasing expertise in diverse architectures, technology stacks, and use cases. • Strong expertise in designing and implementing data warehouse and data lake architectures, particularly in AWS environments. • Extensive experience with Java for data engineering tasks, including familiarity with libraries and frameworks commonly used in Java-based data engineering workflows. • Proven experience with data pipeline orchestration using platforms such as Airflow, Prefect, or AWS Glue. • Hands-on experience with data analysis tools and libraries like NumPy, Pandas, or Dask. • Proficiency with Spark and AWS EMR is highly desirable. • Experience with SQL and NoSQL databases, including PostgreSQL, Amazon Redshift, Delta Lake, and DynamoDB. • In-depth knowledge of data architecture principles and best practices, especially in cloud environments. • Proven experience with AWS services, including expertise in using AWS CLI, SDK, and Infrastructure as Code (IaC) tools such as Terraform, CloudFormation, or AWS CDK. • Exceptional communication skills, capable of clearly articulating complex technical concepts to both technical and non-technical stakeholders. • Demonstrated ability to quickly adapt to new tasks and roles in a dynamic environment.