Job Description:

We are seeking an experienced Data Architect to join our team and take a lead role in designing, developing, and optimizing our data architecture. As a Data Architect, you will play a crucial role in shaping our data strategy by leveraging AWS services such as S3 for data lakes, Redshift, AWS Glue, Informatica, Python for scripting and automation, Snowflake for data warehousing, DBT for modeling, and Fivetran for data integration.

Key Responsibilities:

Design, implement, and maintain Snowflake data warehouse solutions to fulfill business requirements effectively.

Deploy and optimize DBT models and transformations to streamline data processing and facilitate analytics.

Manage Fivetran data pipelines to enable seamless data integration and synchronization.

Utilize AWS Glue for data cataloging, executing ETL jobs, and performing data transformation operations.

Apply Python and SageMaker for advanced analytics, machine learning initiatives, and data science projects.

Employ DB2, SQLServer, and Informatica as necessary for data migration, integration, and administration tasks.

Collaborate with data engineers, analysts, and stakeholders to comprehend data needs and deliver actionable insights.

Develop and enforce data governance and security protocols to uphold data quality and regulatory compliance.

Monitor system performance, troubleshoot issues, and implement performance optimization strategies.

Stay abreast of industry best practices and emerging technologies in data warehousing and cloud computing domains.

Qualifications:

Bachelor's degree in Computer Science, Information Technology, or related field.

Proven experience working with Snowflake, DBT, Fivetran, AWS Glue, Python, SageMaker, DB2, SQLServer, and Informatica technologies in a data engineering or analytics role with 5-6 years of experience.

Certifications in Snowflake, DBT, AWS Glue, Python, SageMaker, or related technologies.

Knowledge of data governance frameworks and data privacy regulations (e.g., GDPR, CCPA).

Strong SQL skills and experience with data modeling, ETL/ELT processes, and data pipeline management.

Familiarity with cloud platforms such as AWS, Azure, or Google Cloud Platform.

Experience with scripting languages (e.g., Python, Bash) for automation and orchestration tasks.

Excellent analytical, problem-solving, and communication skills.

Ability to work independently and collaboratively in a fast-paced environment.