Data Architect

TechDigital Group; Framingham (MA); On-site; USD 90,000 - 150,000; Full time

Job summary

An established industry player seeks a skilled Sr. Data Architect to design and implement innovative data solutions. This role focuses on enhancing customer experiences through advanced analytics and personalized marketing strategies. You will lead the development of scalable data architectures, utilizing cutting-edge technologies like DBT, Snowflake, and Azure. Collaborating with cross-functional teams, you will ensure data governance and quality while integrating new technologies to elevate the organization's data capabilities. If you are passionate about data and eager to make a significant impact, this opportunity is perfect for you.

Qualifications

• 7+ years of experience in Data Architecture or Data Engineering.
• Strong understanding of data modeling and ETL/ELT processes.
• Hands-on experience with Python for data engineering tasks.

Responsibilities

• Architect and implement data solutions for Marketing, Sales, and Customer Service.
• Design and optimize data pipelines for business intelligence and analytics.
• Collaborate with teams to ensure data architectures meet business needs.

Skills

Data Architecture

DBT

Snowflake

Azure

Python

Big Data

Data Governance

ETL/ELT Processes

Data Modeling

Data Warehousing

Education

Bachelor's degree in Computer Science

Master's degree in a related field

Tools

Snowflake

DBT

Azure

Job description

Job Description:

Position Overview:

We are looking for a skilled Sr. Data Architect to design and implement data solutions supporting Marketing, Sales, and Customer Service areas. The ideal candidate will have experience with DBT, Snowflake, Python, and Azure, along with a strong foundation in Big Data and Cloud Platforms. You will be responsible for developing scalable, efficient data architectures that enable personalized customer experiences and advanced analytics.

Key Responsibilities:

1. Architect and implement data solutions across Marketing, Sales, and Customer Service, using technologies such as DBT, Snowflake, and Azure.
2. Design and optimize data pipelines that integrate various data sources (1st party, 3rd party, operational) to support business intelligence and advanced analytics.
3. Develop data models and data flows that enable personalized customer experiences and support omnichannel marketing and customer engagement.
4. Lead efforts to ensure data governance, data quality, and data security, adhering to compliance with regulations such as GDPR and CCPA.
5. Implement and maintain data warehousing solutions in Snowflake to handle large-scale data processing and analytics needs.
6. Optimize workflows using DBT to streamline data transformation and modeling processes.
7. Leverage Azure for cloud infrastructure, data storage, and real-time data analytics, while ensuring the architecture supports scalability and performance.
8. Collaborate with cross-functional teams, including data engineers, analysts, and business stakeholders, to ensure data architectures meet business needs.
9. Support both real-time and batch data integration, ensuring data is accessible for actionable insights and decision-making.
10. Continuously assess and integrate new data technologies and methodologies to enhance the organization's data capabilities.

Qualifications:

1. 7+ years of experience in Data Architecture or Data Engineering, with specific expertise in DBT, Snowflake, and Azure.
2. Strong understanding of data modeling, ETL/ELT processes, and modern data architecture frameworks.
3. Experience designing scalable data architectures for personalization and customer analytics across marketing, sales, and customer service domains.
4. Expertise with cloud data platforms (Azure preferred) and Big Data technologies for large-scale data processing.
5. Hands-on experience with Python for data engineering tasks and scripting.
6. Proven track record of building and managing data pipelines and data warehousing solutions using Snowflake.
7. Familiarity with Customer Data Platforms (CDP), Master Data Management (MDM), and Customer 360 architectures.
8. Strong problem-solving skills and ability to work with cross-functional teams to translate business requirements into scalable data solutions.
9. Bachelor's degree in Computer Science, Data Engineering, or a related field; Master's degree preferred.

Preferred:

1. Experience working with AI/Client models for customer analytics and personalization.
2. Knowledge of data privacy and compliance regulations (GDPR, CCPA).