Big Data Engineer

7 days ago

India Hexaware Technologies Full time

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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