[Hiring] Senior Analyst, Data Engineer @Scotts Miracle-Gro

Role Description

The Senior Analyst in Data Engineering is a technical role that supports data processing and integration efforts. You'll use your advanced analytical skills to improve data pipelines and ensure data delivery is consistent across projects. This role bridges the gap between data engineers and data analysts/scientists to optimize data-driven initiatives.

In this role you will:

• Data Processing and Transformation:
  • Perform data extraction, transformation, and loading (ETL) processes.
  • Design and implement complex data transformation logic to meet business requirements.
  • Ensure the accuracy and reliability of data processing tasks.
• Data Quality and Validation:
  • Implement and execute data quality checks to identify and address anomalies.
  • Collaborate with stakeholders to define and enforce data quality standards.
  • Monitor and troubleshoot data quality issues to maintain high standards.
• Database Management:
  • Manage and optimize databases to support efficient data storage and retrieval.
  • Implement database schemas, indexes, and structures for optimal performance.
  • Collaborate with database administrators to ensure database integrity and security.
• Reporting and Analytics Support:
  • Support data analysts and data scientists in creating reports and analytics solutions.
  • Collaborate with business intelligence teams to integrate data for reporting purposes.
  • Ensure data availability and accuracy for analytical purposes.
• Collaboration with Data Scientists:
  • Work closely with data scientists to understand their data requirements and provide support.
  • Assist in the integration of machine learning models into data engineering pipelines.
  • Optimize data processing for machine learning tasks.
• Process Automation:
  • Identify opportunities for process automation within data engineering workflows.
  • Implement automation scripts and tools to streamline repetitive tasks.
  • Enhance operational efficiency through the use of automation.
• Documentation and Knowledge Sharing:
  • Document data engineering processes, workflows, and best practices.
  • Share knowledge and provide training to team members and other stakeholders.
  • Maintain up-to-date documentation for reference and training purposes.

Qualifications

• Bachelors Degree in Computer Science, Engineering, Mathematics, or related technical field.
• Required: Databricks, Python, Spark SQL, Airflow.
• Desired: AWS Certified Data Engineer.
• 4-7 years of experience preferred.
• 6+ years of experience in Data Engineering.
• Strong communication skills to timely and effectively convey information and consult with others.

Requirements

• 6+ years of developing and maintaining data pipelines (ETL/ELT).
• 6+ years of programming experience in Databricks, Python, and Apache Spark.
• Experience with Apache Airflow.
• Experience in deploying solutions in AWS Cloud with emphasis on Amazon S3, Glue, Athena, EMR, RDS, and lake formation.
• Experience in data modeling and writing complex SQL queries.

Benefits

• Live Total Health program with options for medical, dental, and vision coverage for you, your spouse/domestic partner, and dependents.
• Outstanding wellness reimbursement program.
• 401K match (up to 7.5%).
• 15% discount on company stock.
• Access to Maven Family Planning with up to $30,000 to accommodate for adoption, fertility, and surrogacy.
• Employee Resource Groups focusing on diversity and inclusion, family, education, and sustainability.
• Strong belief in giving back to the communities where we live and work.