Data Architect - California, United States - Insight Global

Insight Global California, United States

3 weeks ago

Description

Title: Sr Data Architect

Location: Sitting anywhere in the Bay Area, Santa Rosa, Sacramento

Full time Salary: 175k-180k

Length: 6 month C2H

Openings: 1

Must Haves:

Industry alignment should be Manufacturing, Logistics, Ops, no Big Tech

Bachelor's in Computer Science, Information Systems, or a related field.

10+ yrs experience working as a data architect, data engineer or in a similar role, designing and implementing data architectures and solutions.

Strong proficiency in data modeling, database design, and SQL, with experience working with relational databases

Expertise in data integration technologies and ETL tools (e.g., Informatica, Talend, Apache NiFi).

Familiarity with data warehousing concepts, methodologies, and technologies

Experience with cloud platforms and services (e.g., AWS, Azure, Google Cloud Platform) and knowledge of cloud-based data storage and processing solutions.

Knowledge of data governance principles, data security, privacy regulations (e.g., GDPR, CCPA), and compliance requirements.

Strong communication and interpersonal skills, with the ability to collaborate effectively with diverse teams and stakeholders.

Certification in data management or related field (e.g., Certified Data Management Professional, AWS Certified Solutions Architect).

Experience with big data technologies and frameworks

Knowledge of data visualization tools and techniques

Familiarity with agile methodologies and DevOps practices

Experience in industries with complex data environments

Plusses:

Master's degree in Computer Science, Information Systems, or a related field.

Day to Day:

Design and develop robust, scalable, and flexible data architectures that align with business objectives and support current and future data needs – from scratch

Define data architecture standards, principles, and best practices to guide the development and implementation of data solutions.

Create conceptual, logical, and physical data models that capture business requirements and facilitate efficient data storage, retrieval, and analysis.

Implement data modeling techniques to optimize performance, ensure data integrity, and enable data integration across disparate systems and platforms.

Establish data governance policies, procedures, and standards to ensure data quality, security, privacy, and compliance with regulatory requirements.

Define data management processes for data ingestion, storage, transformation, and dissemination, including data lifecycle management and metadata management.

Design and implement data integration solutions to consolidate data from multiple sources, transform it into usable formats, and load it into target systems or data warehouses.

Building ETL solutions - Develop and optimize Extract, Transform, Load (ETL) processes to streamline data movement and transformation workflows.

Collaborate with business analysts, leadership, business intelligence to understand reporting and analytics requirements and design data structures that support ad-hoc querying, reporting, and analytics.

Optimize data structures and queries for performance and efficiency to enable real-time or near-real-time analytics and reporting capabilities.

Evaluate emerging technologies, tools, and platforms in the data management space and make recommendations for adoption based on business needs and industry trends.

Lead the implementation and configuration of data management solutions, including databases, data warehouses, data lakes, ETL tools, and BI/reporting tools.

Architect cloud-based data solutions leveraging platforms such as AWS, Azure, or Google Cloud Platform.

Lead the migration of on-premises data systems to cloud environments, ensuring scalability, reliability, and cost efficiency.

Collaborate with cross-functional teams, including business stakeholders, IT professionals, developers, and analysts, to understand requirements, resolve issues, and deliver high-quality data solutions.

Establish data governance frameworks, policies, and standards to ensure data quality, privacy, security, and compliance with regulatory requirements.

Implement security measures to protect sensitive data assets and mitigate cybersecurity risks.

Communicate complex technical concepts and solutions to non-technical stakeholders in a clear and understandable manner.

Will manage a team of Data Engineer and Power BI specialist that they help hire

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