Data Engineer Snowflake
Summary
Data Engineer building and maintaining scalable ETL/ELT pipelines and cloud data warehouses, primarily on Snowflake or Databricks, with Apache Airflow orchestration, SQL/PLSQL tuning, GitLab CI/CD, and cloud storage (AWS S3 / Azure Blob / ADLS). The role also involves data modeling, stakeholder collaboration, and independently handling client interactions.
Role Description
We are looking for an experienced Data Engineer to join our growing data team. The ideal candidate will have strong expertise in data warehousing, ETL development, orchestration tools, cloud platforms, and SQL/PLSQL programming. You will be responsible for designing, developing, and maintaining scalable data pipelines while collaborating with business stakeholders and technical teams to deliver robust data solutions.
Key Responsibilities
- Design, develop, and maintain scalable ETL/ELT pipelines and data integration solutions.
- Build and optimize data warehouse solutions using Snowflake or Databricks.
- Develop and manage workflow orchestration using Apache Airflow.
- Perform data modeling and database design to support business requirements.
- Optimize SQL/PLSQL queries and perform performance tuning for large-scale data processing.
- Implement CI/CD pipelines and deployment processes using GitLab.
- Work with cloud storage solutions such as AWS S3, Azure Blob Storage, or ADLS.
- Collaborate with business stakeholders to gather requirements and translate them into technical solutions.
- Present technical solutions and architectural recommendations to architects and client stakeholders.
- Ensure data quality, governance, scalability, and platform stability.
- Participate in technology exploration and contribute to innovation initiatives.
- Improve monitoring, alerting, and operational processes for data platforms.
- Independently handle client interactions and work closely with cross-functional teams.
Must-Have Skills
- Strong experience with Snowflake or Databricks
- Expertise in Apache Airflow (Orchestration)
- Strong understanding of ETL/ELT processes
- Experience in Data Modeling
- Strong SQL/PLSQL programming skills
- Experience with CI/CD pipelines, deployment processes, and GitLab
- Cloud fundamentals with experience in:
- AWS S3 (Preferred)
- Azure Blob Storage
- Azure Data Lake Storage (ADLS)
- Experience with AWS, Azure, or GCP cloud platforms
Good-to-Have Skills
- PostgreSQL
- Python and Pytest
- Kafka
- Schema Versioning Tools:
- Liquibase
- Flyway
- Runway
- AWS Services:
- Aurora
- RDS
- Lambda (Serverless)
- Maven
- Jira
Preferred Candidate Profile
- 5–10 years of experience in Data Engineering.
- Strong hands-on experience in data warehousing and cloud-based data platforms.
- Experience handling large-scale datasets and performance optimization.
- Ability to work independently and manage client interactions.
- Strong analytical, problem-solving, and communication skills.
- Experience working in Agile development environments.
Why Join Us?
- Opportunity to work on modern cloud-based data platforms.
- Exposure to cutting-edge data engineering technologies.
- Collaborative environment with strong technical leadership.
- Opportunities for learning, innovation, and career growth.