Data Engineer Specialist

3 days ago


Pasig, National Capital Region, Philippines Humanly (humanly) Full time

About TaskUs:

We are a cutting-edge provider of digital services and next-generation customer experience to rapidly growing tech companies. Our mission is to help our clients represent, protect, and grow their brands in an ever-evolving market.

Our People First culture has enabled us to expand our global workforce to approximately 45,000 employees across twelve countries. We have a presence in twenty-three locations, including the Philippines, India, and the United States.

At TaskUs, we understand that achieving growth for our partners requires a culture of constant innovation, exploring new technologies, being ready to handle any challenge at a moment's notice, and mastering consistency in an ever-changing world.

What We Offer:

We prioritize our employees' well-being by offering competitive salaries and comprehensive benefits packages. Our commitment to a People First culture is reflected in the various departments we have established, including Total Rewards, Wellness, HR, and Diversity. We take pride in our inclusive environment and positive impact on the community. Moreover, we actively encourage internal mobility and professional growth at all stages of an employee's career within TaskUs.

Data Engineer Role:

You will be responsible for designing, developing, and maintaining data pipelines and data warehouses for use by the analytics infrastructure. Your role will involve assisting in making accurate and meaningful data available for the consumption of TaskUs Business Intelligence reporting methodology.

Key Responsibilities:

  1. Create new data pipelines, database architectures, and ETL processes, and suggest methodologies.
  2. Gather requirements, perform vendor and product evaluations, deliver solutions, training, and documentation.
  3. Handle design and development, tuning, deployment, and maintenance of information, advanced data analytics, and physical data persistence technologies.
  4. Establish analytic environments for structured, semi-structured, and unstructured data.
  5. Implement business requirements and processes, build ETL configurations, create pipelines for the Data Warehouse, research new technologies, and build proof-of-concepts.
  6. Build and maintain extract-transform-load (

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