| Job opening || AWS Data Engineer || Onsite || Contract at Remote, Remote, USA |
| Email: [email protected] |
| From: iyyappan, Smartitframe [email protected] Reply to: [email protected] Dear, Greetings from Smart IT Frame, Hope you are doing well!!! Smart IT Frame specializes in enabling you with your most critical line of resources. Whether its for permanent staffing, contract staffing, contract-to-hire or executive search, we understand the importance of delivering the most suitable talent; on time and within budget. With our Core focus in emerging technologies, we have provided global technology workforce solutions in North America, Canada & India. We take pride in delivering specialized talent, superior performance, and seamless execution to meet the challenging business needs of customers worldwide. Job Title: Lead AWS Data Engineer Location: Onsite - preferable in Chicago, IL (OR) Austin, TX (OR) Santa Monica, CA Duration: 6+ Months Skills Required: AWS, SQL, PySpark and Databricks Responsibilities: Collaborate with product managers, data scientists, data analysts and engineers to define features needed for a Data Platform Provide mentorship and technical leadership for a team Work closely with other engineers to scale infrastructure, improve reliability and efficiency Improve developer tooling with a focus on reliability and efficiency Write good technical documentation Perform large system upgrades and migrations Maintenance and improvement of multiple CI/CD pipelines Act as an in-house data expert who makes recommendations regarding standards for code quality and pipeline architecture Develop, deploy and maintain data processing pipelines using cloud technology such as AWS, Kubernetes, Lambda, Kafka, Airflow, Redshift, S3, Glue, and EMR Make smart engineering and infra decisions based on data auditing and collaboration Lead and architect cloud-based data infrastructure solutions to meet stakeholder needs. Skills & Qualifications: 8+ years of professional experience in any one of the Cloud providers such as AWS, Azure or GCP 8+ years experience in engineering data pipelines using data technologies (Python, Databricks, pySpark, Kafka) on large scale data sets Experience building or maintaining a Data Platform that supports multiple engineering teams and processes big data Ability to quickly learn complex domains and new technologies. Innately curious and organized with the drive to analyze data to identify deliverables, anomalies and gaps and propose solutions to address these findings Experience designing data models that have been implemented in production Strong experience in writing complex SQL and ETL development with experience processing large data sets Familiarity with AWS Services (Redshift, RDS, EKS, S3, EMR, Glue, Lambda) Experience using GitHub, Docker, Terraform, CodeFresh, Jira Experience contributing to full lifecycle deployments with a focus on quality and scalability. Good to Have: Experience with customer data platform tools such as Segment Experience contributing to full lifecycle deployments with a focus on testing and quality Experience with data quality processes, data quality checks, validations, data quality metrics definition and measurement AWS/Kafka/Databricks or similar certifications. Keywords: continuous integration continuous deployment sthree information technology California Illinois Texas |
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| Wed Jul 19 20:13:00 UTC 2023 |