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Tredence Analytics - Data Build Tool Developer - SQL
Tredence Analytics - Data Build Tool Developer - SQLTredence Analytics Solutions Private Limited • Gurgaon
Tredence Analytics - Data Build Tool Developer - SQL

Tredence Analytics - Data Build Tool Developer - SQL

Tredence Analytics Solutions Private Limited • Gurgaon
30+ days ago
Job description

As a Data Build tool (DBT) senior developer you will work with team to help designing, building, and maintaining data pipelines and transformations using any cloud and the Data Build Tool (dbt).

This often includes using tools like different cloud tools, and requires strong SQL skills and knowledge of data warehousing concepts.

The role also involves ensuring data quality, performance optimization, and collaborating with cross-functional teams.

Role & responsibilities :

  • Designing, building, and maintaining ETL / ELT pipelines using dbt and any cloud service expertise
  • Creating and managing data models and transformations using dbt to ensure efficient and accurate data consumption for analytics and reporting.
  • Developing and maintaining a data quality framework, including automated testing and cross-dataset validation.
  • Writing and optimizing SQL queries for efficient data processing within BigQuery.
  • Working with data engineers, analysts, scientists, and business stakeholders to deliver data solutions.
  • Supporting day-to-day incident and ticket resolution related to data pipelines.
  • Creating and maintaining comprehensive documentation for data pipelines, configurations, and procedures.
  • Utilizing GCP services like BigQuery, Cloud Composer, Cloud Functions, etc.
  • Developing and maintaining SQL / Python scripts for data ingestion, transformation, and automation tasks.

Preferred candidate profile :

Requirements :

  • Typically requires 8~12 years of experience in data engineering or a related field.
  • dbt Expertise : Proficiency in using dbt for data transformation, testing, and documentation.

    SQL Proficiency : Advanced SQL skills for data modeling, performance optimization, and querying large datasets.

    Data Warehousing : Understanding of data warehousing concepts, dimensional modeling, and star schema design.

    ETL / ELT : Experience with ETL / ELT tools and frameworks, including Apache Beam, Cloud Dataflow, Data Fusion, or Airflow / Composer.

    (ref : hirist.tech)

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