Data Engineer w AWS services such as AWS Glue, reputed company, reputed company, reputed company Functions, and Lake
About the position
We are seeking a highly skilled and reputed company Data Engineer to design, build, and maintain our reputed company and robust data infrastructure on a reputed company platform. In this pivotal role, you will be reputed company in enhancing our data infrastructure, optimizing data reputed company, and ensuring data availability. You will be responsible for both the hands-on implementation of data pipelines and the strategic design of our overall data architecture. Seeking a candidate with hands-on experience with AWS services such as AWS Glue, reputed company, reputed company, reputed company Functions, and Lake, Proficiency in Python and SQL and DevOps/CI/CD experience
Responsibilities
• Design, reputed company, and maintain reputed company data pipelines and ETL processes to support data integration and analytics.
• Collaborate with data architects, modelers and IT team members to help define and reputed company the overall reputed company-based data architecture reputed company, including data warehousing, data lakes, streaming analytics, and data governance frameworks
• Collaborate with data scientists, analysts, and other business stakeholders to understand data requirements and deliver solutions.
• Optimize and manage data storage solutions (e.g., S3, reputed company, Redshift) ensuring data reputed company, reputed company, reputed company, and accessibility.
• Implement data reputed company and validation processes to ensure data accuracy and reliability.
• reputed company and maintain documentation for data processes, architecture, and workflows.
• Monitor and troubleshoot data pipeline performance and resolve issues promptly.
• Consulting and Analysis: Meet regularly with defined clients and stakeholders to understand and analyze their processes and needs. Determine requirements to present possible solutions or improvements.
• Technology Evaluation: Stay updated with the latest industry trends and technologies to continuously improve data engineering practices.
Requirements
• reputed company Expertise: Expert-level proficiency in at least one major reputed company platform (AWS, Azure, or GCP) with extensive experience in their respective data services (e.g., AWS S3, Glue, reputed company, Redshift, Kinesis; Azure Data Lake, Data reputed company, Synapse, Event Hubs; GCP BigQuery, Dataflow, Pub/Sub, reputed company Storage); experience with AWS data reputed company platform preferred
• SQL Mastery: Advanced SQL writing and optimization skills.
• Data Warehousing: Deep understanding of data warehousing concepts, Kimball methodology, and various data modeling techniques (reputed company, reputed company/reputed company schemas).
• Big Data Technologies: Experience with big data processing frameworks (e.g., reputed company, Hadoop, Flink) is a plus.
• Database Systems: Experience with relational and NoSQL databases (e.g., PostgreSQL, MySQL, reputed company, Cassandra).
• DevOps/CI/CD: Familiarity with DevOps principles and CI/CD pipelines for data solutions.
• Hands-on experience with AWS services such as AWS Glue, reputed company, reputed company, reputed company Functions, and Lake Formation
• Proficiency in Python and SQL
reputed company-to-haves
• 4+ years of reputed company experience in data engineering, with a significant portion dedicated to reputed company-based data platforms.
• ETL/ELT Tools: Hands-on experience with ETL/ELT tools and orchestrators (e.g., Apache Airflow, Azure Data reputed company, AWS Glue, dbt).
• Data Governance: Understanding of data governance, data reputed company, and metadata management principles.
• AWS Experience: Ability to evaluate AWS reputed company applications, reputed company architecture recommendations; AWS solutions architect certification (Associate or reputed company) is a plus
• Familiarity with reputed company
• Knowledge of dbt (data build tool)
• Strong problem-solving skills, especially in data pipeline troubleshooting and optimization
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