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Staff Engineer, Analytics Engineering

Stellantis · Auburn Hills, MI, United States

Strong hiring record · median 4 days open

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Posted today · still listed on the employer's own board · How we score

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  • Posted today
  • Still listed on the employer's own board

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Staff Engineer, Analytics Engineering at Stellantis. We’ll keep it in your applied jobs, so you can see it later and be warned before applying to the same employer twice.

Do you have a passion for building innovative data pipelines and transforming raw data into actionable insights? Are you an expert in programming languages like Spark, SQL, and Python, and thrive in a collaborative environment? If so, we want to hear from you!

About the role

We are seeking a talented and experienced Analytics/Data Engineer to join our growing team. In this role, you will play a key part in designing, developing, and maintaining the data pipelines that power our organization's data-driven decision making. You will work closely with data scientists, analysts, and other engineers to ensure that our data infrastructure is reliable, scalable, and secure.

Responsibilities

  • Design, develop, and maintain scalable and efficient data pipelines using Spark, SQL, and Python
  • Utilize Databricks platform to build and manage data processing workflows
  • Clean, transform, and integrate data from various sources into a unified and consistent format
  • Implement data quality checks and monitoring processes to ensure data accuracy and completeness
  • Collaborate with data scientists and analysts to understand their data needs and develop solutions
  • Document data pipelines and processes using clear and concise language
  • Utilize Git for version control and maintain a clean and collaborative development environment
  • Follow software development best practices, including unit testing, code reviews, and continuous
  • integration/continuous delivery (CI/CD)
  • Stay up to date with the latest advancements in data engineering technologies and best practices.

Basic Qualifications

  • Bachelor's degree in Computer Science, Information Technology, or a related field
  • Minimum 5 years of experience as a Data Engineer or similar role
  • Strong proficiency in SQL, Python, and Spark
  • Familiarity with Databricks platform
  • Experience with data warehousing and data lakes (e.g., AWS Redshift, Snowflake) is a plus
  • Experience with Git and software development best practices (unit testing, code reviews, CI/CD)
  • Experience leveraging Gen AI tooling.
  • Excellent communication and collaboration skills
  • Ability to work independently and as part of a team

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