Data Engineer

4 weeks ago

Lahore, Punjab, Pakistan Tandeminvest Full time

About Burq

Burq started with an ambitious mission: to simplify the complex process of offering delivery through a turnkey solution.

We built the largest network of delivery partners, making it easy for businesses to plug into our network and start offering delivery services. Currently, we power deliveries for some of the fastest-growing companies, from retailers to startups.

We are backed by leading venture capitalists, including Village Global, with investors like Bill Gates, Jeff Bezos, Mark Zuckerberg, Reid Hoffman, and Sara Blakely. Our team is composed of world-class professionals across the U.S.

While we operate at scale, we are still a small team with a significant growth opportunity. This presents an excellent chance for you to develop your career while contributing to impactful work.

We seek individuals unafraid of being wrong, who support decisions with data and narrative. Here's an overview of your responsibilities:

Some of the responsibilities

  • Design, build, and maintain scalable data pipelines using tools like Airbyte, Airflow, and dbt, with a focus on Snowflake integration.
  • Manage and optimize data warehousing solutions with Snowflake, ensuring data security, organization, and accessibility.
  • Develop automations and workflows to streamline data processing and integration for seamless data flow.
  • Collaborate with cross-functional teams to establish and maintain data infrastructure supporting engineering and analytics.
  • Utilize Databricks and Spark for big data processing, ensuring efficient data storage, processing, and analysis.
  • Monitor data streams and processes with Kafka and Monte Cristo to ensure data quality and integrity.
  • Work with data analysts and stakeholders to create, maintain, and optimize visualizations and reports using Tableau for data-driven decisions.
  • Ensure data system security and compliance, applying best practices and tools like Terraform for infrastructure management.
  • Continuously evaluate and improve data processes, staying updated with industry best practices and emerging technologies, especially in data analytics and visualization.
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