Cloud Data Architect -ELT AWS Snowflake with Security Clearance

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