Data Engineer

Roles & Responsibilities:

• Manage the analytics data warehouse and implement analytical database design principles and business process best practices.
• Develop and support data pipelines, data lake, and data warehouse solutions; unlock value from data to support business decisions.
• Deliver clean data sets and products to product owners, analytics teams, and end users.
• Model data to create straightforward data APIs enabling front-end developers to connect visual components easily.
• Maintain and monitor data pipeline services and business intelligence platforms.
• Apply engineering best practices to deliver well-defined, tested, documented, and code-reviewed shared data sets.
• Identify, design, and implement process improvements—automation, optimizing data delivery, and infrastructure redesign for scalability.
• Support analytical requests cross-functionally from internal and external stakeholders.
• Create and maintain optimal data pipeline architecture.
• Assemble complex data sets meeting functional and non-functional business requirements.
• Build infrastructure for data extraction, transformation, and loading from diverse sources using ingestion techniques and AWS technologies.
• Develop data tools for analytics and data science teams to build and optimize products as industry leaders.
• Collaborate with data and analytics experts to enhance functionality in data systems.
• Establish scalable, efficient, automated processes for large-scale data analyses, model development, validation, and implementation.
• Solve complex data challenges and deliver actionable insights to achieve business goals.
• Create data products that boost analytics and data scientist productivity.

Skill Set Required:

Must have:

• Experience developing data solutions on cloud computing platforms, preferably GCP.
• 2+ years hands-on experience with frameworks such as Python, Java, or Scala.
• Skills in Python; Google BigQuery, Google Storage, Cloud Composer, Dataflow; Google PubSub; SQL; Ansible; Tableau APIs; Jenkins; and Shell scripting.

Nice to have:

• Experience with Data Warehouse and ETL migrations.
• Advanced SQL skills and familiarity with various relational databases and complex query authoring.
• Experience with Scala, Python, PySpark, Java, REST API, Microservices, etc.
• Experience in restaurant or retail operations is preferred but not mandatory.