Junior Snowflake Data Engineer

We don't need a senior person here as the rate is offered for this role is not on higher side.

Job Title: Junior Snowflake Data Engineer

Location: Remote

Required Experience: 6+ years

Duration: 6 Month+

Need someone focused on Snowflake and DBT along with Python, and Airflow.

About the Role:

We are seeking a 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.