Big Data Engineer
1 month ago
Experience : 4-6yrs
Work location : Bangalore/Pune/Chennai/Coimbatore/Mumbai
Notice Period : Immediate - 30 days
Primary - Snowflake, Advance SQL, ETL Concepts
Secondary - dbt (Data Build Tool), Prefect/Airflow or a similar orchestration tool
Job Description:
We are on the looking for a Data Engineer with a solid foundation in Snowflake and a proficient background in dbt (data build tool), workflow orchestration tools (Prefect or Airflow), and advanced SQL.
With over 5 years of experience in the data engineering field, the ideal candidate will play a pivotal role in architecting, developing, and optimizing our data infrastructure to support scalable business intelligence and analytics solutions.
Required Qualifications:
- Bachelor’s or master’s degree in computer science, Information Systems, Data Science, or a related discipline.
- A minimum of 5 years of professional experience in data engineering, with specific expertise in Snowflake.
- Demonstrated experience in developing data transformation processes with dbt and orchestrating workflows with Prefect or Airflow.
- Advanced proficiency in SQL, with a track record of performing complex data analyses and optimizations.
- Extensive knowledge in data modelling and experience in designing data architectures for scalability and performance.
- Proven ability to troubleshoot and optimize data processes, with a keen eye for data quality and integrity.
- Excellent collaborative and communication skills, capable of working cross-functionally and articulating technical concepts to non-technical stakeholders.
Key Responsibilities:
- Design and implementation of scalable data models within Snowflake to accommodate evolving business needs.
- ETL Pipeline Management: Craft, manage, and optimize ETL processes using dbt, ensuring high data quality and process efficiency.
- Workflow Orchestration: Employ Prefect or Airflow to manage data workflow orchestration, achieving seamless, automated, and error-free data operations.
- Complex Data Analysis: Utilize advanced SQL for in-depth data analysis, providing actionable insights and supporting strategic decision-making.
- Data Integrity Assurance: Implement rigorous data quality frameworks to ensure the accuracy and reliability of data across pipelines.
- Cross-functional Collaboration: Serve as the go-to data engineering expert, collaborating with stakeholders across functions to define data needs and deliver comprehensive data solutions.
- Performance Tuning: Monitor and fine-tune performance within Snowflake, dbt, and orchestration platforms to ensure cost-effectiveness and operational efficiency.
- Stay at the forefront of data engineering practices, advocating for and adopting innovative technologies and methodologies to enhance our data ecosystem.
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