Architect and implement advanced data solutions and acquisition pipelines using Snowflake on AWS. Lead the migration of workloads from Cloudera to Snowflake and develop data products leveraging ML and LLMOps capabilities.

Requirements

Requires over 8 years of experience in data architecture and engineering, specifically with Snowflake, AWS Glue, and dbt. Proficiency in SQL, Python, and experience with Medallion Architecture in financial or insurance sectors is essential.

Experience

10+ years

Education

professional certificate

Working hours

40 hours per week

Job type

Contract

Work arrangement

On-site

Skills

Snowflake
AWS Glue
Apache Airflow
dbt
AWS
Data Architecture
Python
SQL
Data Modeling
Lakehouse
Medallion Architecture
Streamlit
LLMOps
Cloudera
Informatica
Data Governance

Visa sponsorship

Not detected in the job text

Keywords

Snowflake
AWS
AWS Glue
Apache Airflow
dbt
Lakehouse
Medallion Architecture
Cloudera
AWS Redshift
Informatica
IDMC
PowerCenter
BDM
Streamlit
MLOps
LLMOps
SnowPro Advanced
SQL
Python
Java
Data Modeling
ETL
ELT
Data Governance
Collibra
Data Lifecycle Management
AWS ECS
Insurance
Financial Services
Data Pipelines

Original job description

Extensive experience (8+ years) in data architecture and engineering, with a proven track record in large-scale data transformation programs, ideally in insurance or financial services.
Proven experience in architecting and implementing advanced data solutions using Snowflake on AWS.
Expertise in designing and orchestrating data acquisition pipelines using AWS Glue for ETL/ELT, Snowflake Openflow, and Apache Airflow for workflow automation, enabling seamless ingestion of data from diverse sources.
Proven experience with dbt to manage and automate complex data transformations within Snowflake, ensuring modular, testable, and version-controlled transformation logic.
Experience implementing Lakehouse solutions and Medallion Architecture for financial or insurance carriers.
Experience optimizing and tuning Snowflake environments for performance, cost, and scalability, including query optimization and resource management.
Experience in architecting and/or leading migration of workloads from Cloudera to Snowflake.
Experience designing Streamlit applications and defining new capabilities and data products leveraging Snowflake ML and LLMOps capabilities.
Experience evaluating data technology platforms, including data governance suites and data security products.
Exposure to enterprise Data Warehouse solutions such as Cloudera and AWS Redshift, as well as Informatica toolsets, including IDMC, PowerCenter, and BDM.
Ability to develop robust data models and data pipelines to support data transformation, integrating multiple data sources while ensuring data quality and integrity.
Ability to document architecture, data flows, and transformation logic to ensure transparency, maintainability, and knowledge sharing across teams.
Strong knowledge of data lifecycle management, data retention, and data modeling, along with working knowledge of cloud computing and modern development practices.
Experience with data governance, metadata management, and data quality frameworks, such as Collibra and Informatica.
Experience in converting policy/data from legacy platforms to modern platforms.
Deep expertise in Snowflake; SnowPro Advanced certification preferred, with hands-on experience delivering Snowflake as an enterprise capability.
Hands-on experience with AWS Glue for ETL/ELT, Apache Airflow for orchestration, and dbt for transformation, preferably deployed on AWS ECS.
Proficiency in SQL, data modeling, ETL/ELT processes, and scripting languages such as Python/Java.

Apply by Oct 11, 2026

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