Senior Data Engineer

• Design, build and maintain batch or real-time data pipelines in production. 
• Maintain and optimize the data infrastructure required for accurate extraction, transformation, and loading of data from a wide variety of data sources.
• Develop ETL (extract, transform, load) processes to help extract and manipulate data from multiple sources. 
• Automate data workflows such as data ingestion, aggregation, and ETL processing. 
• Prepare raw data in Data Warehouses into a consumable dataset for both technical and non-technical stakeholders. 
• Partner with data scientists and functional leaders in sales, marketing, and product to deploy machine learning models in production. 
• Build, maintain, and deploy data products for analytics and data science teams on cloud platforms (e.g. AWS, Azure, GCP). 
• Ensure data accuracy, integrity, privacy, security, and compliance through quality control procedures.
• Monitor data systems performance and implement optimization strategies.
• Leverage data controls to maintain data privacy, security, compliance, and quality for allocated areas of ownership. 

You have what it takes if you have…

• Advanced SQL skills and experience with relational databases and database design. 
• Experience working with cloud Data Warehouse solutions – Databricks, Apache Spark
• Experience working with data ingestion tools such as Fivetran, stitch, or Matillion. 
• Working knowledge of Cloud-based solutions (e.g. AWS, Azure, GCP). 
• Experience building and deploying machine learning models in production. 
• Strong proficiency in object-oriented languages: Python, Java, C++, Scala. 
• Strong proficiency in scripting languages like Bash. 
• Strong proficiency in data pipeline and workflow management tools (e.g., Airflow). 
• Strong project management and organizational skills. 
• Excellent problem-solving, communication, and organizational skills. 
  • Proven ability to work independently and with a team.