Senior Cloud Data Lead

4 weeks ago


Denver, United States CareerBuilder Full time

As a Senior Cloud Data Lead, you will play a pivotal role in owning the organizations data architecture and will be responsible for designing, building, implementing, and managing this architecture across all applications within the enterprise. The role demands a strong understanding of data modeling, database management, data warehousing, and data integration techniques, requiring impeccable communication skills and attention to detail. Additionally, you will collaborate closely with stakeholders, including data engineers, analysts, and business leaders, to ensure that data architecture aligns with organizational data strategy and requirements.
ESSENTIAL ROLES AND RESPONSIBILITIES

Design enterprise data management systems that will provide data insights to support the business in order to make key decisions
Identify key systems of record and modernize data flow to support it
Develop and implement the organization's data architecture strategy, including conceptual, logical, and physical data models, ensuring alignment with business goals and industry best practices
Oversee the selection, implementation, and optimization of all data systems, ensuring efficient data storage, retrieval, and integrity
Establish data governance policies, procedures, and standards to ensure data quality, cost, consistency, privacy, and security throughout the data lifecycle
Identify and address performance bottlenecks within the data architecture through optimization techniques, indexing strategies, and data partitioning
Collaborate with cross-functional teams, including data engineers, analysts, developers, and business stakeholders, to understand requirements, define data architecture solutions, and communicate technical concepts effectively
Stay abreast of emerging trends and technologies in data management, analytics, and cloud computing, evaluating their potential impact on the organization's data architecture and recommending adoption strategies accordingly
Maintain comprehensive documentation of data architecture artifacts, including data models, data dictionaries, metadata repositories, and technical specifications
Continuously assess and refine the data architecture framework, processes, and standards to enhance scalability, reliability, and performance in alignment with evolving business needs and technological advancements
Support and advocate for process improvement to result in higher quality data assets throughout organization
EDUCATION, SKILLS, AND EXPERIENCE

Bachelor's or Master's degree in Computer Science, Information Systems, or related field
Technical data lead with 5+ years experience in a similar role
Understands SOA and AWS Cloud
Understands Data Science, Reporting, and Orchestration concepts and can put into practice for a travel company
In-depth knowledge of data modeling principles, techniques, and modern tools (e.g., ER/Studio, PowerDesigner)
Proficiency in database management systems, including relational databases (e.g., Oracle, SQL Server, MySQL) and NoSQL databases (e.g., MongoDB, Cassandra)
Hands-on experience with data integration tools and technologies (e.g., ETL/ELT, APIs, messaging queues, Informatica, Talend, AWS Glue, AWS Step Functions, Fivetran, and Apache Airflow)
Strong understanding of data governance, security, and compliance requirements (e.g., GDPR, HIPAA, PCI DSS)
Familiarity with cloud platforms (e.g., AWS, Azure) and their data services (e.g., S3, Redshift, BigQuery)
Self-starter with excellent analytical, problem-solving, and decision-making skills with a keen attention to detail
Effective communication and interpersonal skills, with the ability to collaborate across diverse teams and stakeholders
Proven ability to manage multiple priorities and deliver results in a fast-paced, dynamic environment
PREFERRED QUALIFICATIONS

Certification in data management or related field (e.g., AWS Certified Data Analytics Professional, AWS Certified Database Specialty, CDMP)
Experience with data visualization and business intelligence tools (e.g., Tableau, Power BI, Qlik)
Snowflake SnowPro certification in a plus
Knowledge of machine learning and predictive analytics concepts and techniques
Familiarity with agile methodologies and DevOps practices in the context of data architecture and engineering

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