Senior Data Transformation Specialist

6 days ago


San Francisco, California, United States Tbwa ChiatDay Inc Full time
Job Description

We are seeking a skilled Senior Data Transformation Specialist to join our team in Poland. This role involves analyzing, cleaning, and transforming customer data into standardized, high-quality datasets that power our business operations.

Key Responsibilities
  • Partner with the sales team to integrate new customers into our system and manage roll-out timelines.
  • Design and implement data transformation processes to convert customer data into our required formats and schemas.
  • Analyze complex customer data structures and formats to determine optimal transformation strategies.
  • Develop and maintain ETL pipelines for efficient customer data ingestion and transformation.
  • Perform thorough data quality assessments and implement data cleaning procedures to ensure accuracy and consistency of transformed data.
  • Optimize data transformation queries and processes for improved performance across multiple database technologies.
  • Collaborate with cross-functional teams to understand customer data requirements and deliver effective transformation solutions.
Requirements
  • Bachelor's or Master's degree in Computer Science, Data Engineering, or related field.
  • 5+ years of experience in data engineering with a focus on data transformation and integration.
  • Proficiency in at least three of the following database technologies: MySQL, Redis, Google BigQuery, MongoDB.
  • Strong skills in data profiling, cleansing, and transformation techniques.
  • Proficiency in Python and SQL for complex data manipulation and transformation.
  • Experience with ETL tools and frameworks for large-scale data processing.
Salary and Benefits

The estimated salary range for this position is $120,000 - $140,000 USD annually, plus stock options. We offer competitive salaries, paid time off, quarterly team retreats, access to modern data processing tools and technologies, professional development opportunities, and a collaborative work environment focused on data quality and efficiency.



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