Negotiable
Outside
Remote
USA
Summary: We are looking for a Senior Data Engineer specializing in Snowflake, DBT, and Airflow to develop and optimize cloud data platforms. The role involves designing ETL/ELT pipelines, managing data across various layers, and ensuring compliance with data governance standards. The ideal candidate will have extensive experience in data engineering and a strong understanding of data modeling and orchestration frameworks. This position is fully remote and requires a minimum of three years of experience in the US.
Key Responsibilities:
- Design and implement end-to-end data pipelines using Snowflake, DBT, Airflow, and Python.
- Ingest data from diverse sources (transaction systems, APIs, streaming platforms like Kafka) into cloud data platforms (AWS, Azure, Google Cloud Platform).
- Manage data across bronze, silver, and gold layers ensuring scalability, lineage, and compliance.
- Develop and optimize data models (star schema, Data Vault, SCD handling) for analytics and reporting use cases.
- Build reusable frameworks for data ingestion, transformation, and quality checks.
- Define and manage Airflow DAGs with dependencies, retries, SLAs, and monitoring.
- Implement CI/CD pipelines for DBT and Airflow jobs using GitLab/Jenkins.
- Ensure data governance, masking, encryption, and regulatory compliance (HIPAA, GDPR, SOX, PCI DSS).
- Collaborate with cross-functional teams (Data Architects, BI Developers, Data Scientists) to deliver business-ready datasets.
- Troubleshoot pipeline failures, optimize query performance, and ensure 99.9% pipeline reliability.
Key Skills:
- 6+ years of professional experience in Data Engineering.
- Hands-on expertise with Snowflake (warehousing, task automation, RBAC, query optimization).
- Proficiency in DBT (models, macros, testing, documentation, dbt Cloud/CLI).
- Strong experience with Apache Airflow (DAG design, custom operators, retries, SLAs, alerting).
- Advanced SQL and Python programming skills.
- Experience with AWS services (S3, Glue, Lambda, EMR, RDS, Kinesis, MSK).
- Familiarity with streaming technologies (Kafka, Spark Streaming).
- Strong understanding of data modeling, ETL/ELT frameworks, and pipeline orchestration.
- Knowledge of DevOps practices (CI/CD, Terraform, Docker, GitLab/Jenkins).
- Excellent problem-solving and communication skills; ability to explain technical solutions in business terms.
Salary (Rate): undetermined
City: undetermined
Country: USA
Working Arrangements: remote
IR35 Status: outside IR35
Seniority Level: Senior
Industry: IT
Title : Snowflake Data Engineer
Type : Remote
Visa : , ,, OPT
Primary Skills : Snowflake , DBT , Python & Airflow
Interview : 2-3 rounds of Interviews
We are seeking a Senior Data Engineer with strong expertise in Snowflake, DBT, and Airflow to design, build, and optimize modern cloud data platforms. The ideal candidate has hands-on experience with ETL/ELT pipelines, data modeling, and orchestration frameworks, and can translate business requirements into scalable, secure, and performant data solutions.
Key Responsibilities:
- Design and implement end-to-end data pipelines using Snowflake, DBT, Airflow, and Python.
- Ingest data from diverse sources (transaction systems, APIs, streaming platforms like Kafka) into cloud data platforms (AWS, Azure, Google Cloud Platform).
- Manage data across bronze, silver, and gold layers ensuring scalability, lineage, and compliance.
- Develop and optimize data models (star schema, Data Vault, SCD handling) for analytics and reporting use cases.
- Build reusable frameworks for data ingestion, transformation, and quality checks.
- Define and manage Airflow DAGs with dependencies, retries, SLAs, and monitoring.
- Implement CI/CD pipelines for DBT and Airflow jobs using GitLab/Jenkins.
- Ensure data governance, masking, encryption, and regulatory compliance (HIPAA, GDPR, SOX, PCI DSS).
- Collaborate with cross-functional teams (Data Architects, BI Developers, Data Scientists) to deliver business-ready datasets.
- Troubleshoot pipeline failures, optimize query performance, and ensure 99.9% pipeline reliability.
Required Skills & Experience:
- 6+ years of professional experience in Data Engineering.
- Hands-on expertise with Snowflake (warehousing, task automation, RBAC, query optimization).
- Proficiency in DBT (models, macros, testing, documentation, dbt Cloud/CLI).
- Strong experience with Apache Airflow (DAG design, custom operators, retries, SLAs, alerting).
- Advanced SQL and Python programming skills.
- Experience with AWS services (S3, Glue, Lambda, EMR, RDS, Kinesis, MSK).
- Familiarity with streaming technologies (Kafka, Spark Streaming).
- Strong understanding of data modeling, ETL/ELT frameworks, and pipeline orchestration.
- Knowledge of DevOps practices (CI/CD, Terraform, Docker, GitLab/Jenkins).
- Excellent problem-solving and communication skills; ability to explain technical solutions in business terms.
Preferred Qualifications
- Prior experience in Healthcare, Finance, or Retail domains.
- Familiarity with Redshift, Databricks, or BigQuery.
- Exposure to data governance tools (Collibra, Alation).
- Experience with real-time analytics use cases (fraud detection, patient monitoring, stockouts reduction).
- Certification in Snowflake, AWS, or DBT.
Note - Minimum 3 years US experience
If interested , please share your resume at
#Snowflake #DBT #Python #AWS #W2 #Immedidate_Join #Urgent