Cloud Data Architect -ELT AWS Snowflake with Security Clearance

Anonymous Employer

Redding Ridge, CT

Apply

JOB DETAILS

SKILLS

AWS Lambda, Amazon Simple Storage Service (S3), Amazon Web Services (AWS), Analysis Skills, Apache, Apache Cassandra, Apache Hadoop, Apache Spark, Big Data, Cloud Applications, Cloud Architecture, Cloud Computing, Cloud Storage, Computer Science, Consulting, Continuous Deployment/Delivery, Continuous Improvement, Continuous Integration, Data Analysis, Data Lake, Data Management, Data Modeling, Data Processing, Data Quality, Data Science, Data Storage, Data Warehousing, Data Warehousing Applications, DataArchitect Data Modeling Tool, Database Extract Transform and Load (ETL), Database Technology, DevOps, Documentation, GCP (Good Clinical Practices), Hubs, Identify Issues, Industry/Trade Analysis, Information Technology & Information Systems, Management of Information Systems/Technology (MIS), Metadata, Microsoft Windows Azure, MongoDB, MySQL, Needs Assessment, NoSQL, PostgreSQL, Problem Solving Skills, Process Analysis, Project/Program Management, Python Programming/Scripting Language, Quality Management, Relational Databases (RDBMS), SQL (Structured Query Language), Scalable System Development, Security Clearance, Snowflake Schema, Software Development Lifecycle (SDLC), Software Engineering, Star Schema, Team Player, Technology Analysis

LOCATION

Redding Ridge, CT

POSTED

Today

Duties & Responsibilities
• Design, develop, and maintain scalable data pipelines and ETL processes to support data integration and analytics.
• Collaborate with data architects, modelers and IT team members to help define and evolve the overall cloud-based data architecture strategy, 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, Snowflake, Redshift) ensuring data quality, integrity, security, and accessibility.
• Implement data quality and validation processes to ensure data accuracy and reliability.
• Develop 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
Data Engineer
• Associate degree in Computer Science or MIS with a minimum of 4 years experience; or Bachelor degree in Computer Science, or MIS, or related field with a minimum of 2 years of experience; or a Master degree in Computer Science, MIS, with minimum 1 year of experience; or relevant Business or IT experience of minimum of 4 years.
• Moderate level of technical understanding and demonstrated knowledge in integrating data between applications and data warehouses
• Knowledge of project management and experience working on project teams required.
• Moderate knowledge of and experience with life cycle methodology,
• Exposure to or experience in Expertise in one or more of a major cloud platform (AWS, Azure or GCP)
• Moderate knowledge of and experience with the software development lifecycle.
• Experience working in project teams and contributing to a successful outcome
• Hands-on experience with AWS services such as AWS Glue, Lambda, Athena, Step Functions, and Lake Formation
• Proficiency in Python and SQL
Sr. Data Engineer • Associate degree in Computer Science, MIS or related field with a minimum of 8 years experience; or Bachelor degree in Computer Science, or MIS, or related field with minimum of 4 years of experience; or a Master degree in Computer Science, MIS, or related field with minimum 2 years of experience; or relevant Business or IT experience of minimum of 4 years.
• Cloud Expertise: Expert-level proficiency in at least one major cloud platform (AWS, Azure, or GCP) with extensive experience in their respective data services (e.g., AWS S3, Glue, Lambda, Redshift, Kinesis; Azure Data Lake, Data Factory, Synapse, Event Hubs; GCP BigQuery, Dataflow, Pub/Sub, Cloud Storage); experience with AWS data cloud 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 (dimensional, star/snowflake schemas).
• Big Data Technologies: Experience with big data processing frameworks (e.g., Spark, Hadoop, Flink) is a plus.
• Database Systems: Experience with relational and NoSQL databases (e.g., PostgreSQL, MySQL, MongoDB, 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, Lambda, Athena, Step Functions, and Lake Formation
• Proficiency in Python and SQL
• Desired Skills, Experience and Abilities
• 4+ years of progressive experience in data engineering, with a significant portion dedicated to cloud-based data platforms.
• ETL/ELT Tools: Hands-on experience with ETL/ELT tools and orchestrators (e.g., Apache Airflow, Azure Data Factory, AWS Glue, dbt).
• Data Governance: Understanding of data governance, data quality, and metadata management principles.
• AWS Experience: Ability to evaluate AWS cloud applications, make architecture recommendations; AWS solutions architect certification (Associate or Professional) is a plus
• Familiarity with Snowflake
• Knowledge of dbt (data build tool)
• Strong problem-solving skills, especially in data pipeline troubleshooting and optimization

About the Company

Anonymous Employer

Resume Resources

Free Resume Templates Free Resume Builder