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Open nowFirst seen 6 hours ago

Data Engineer | Hybrid Setup

HRTX1,659 open roles

Work mode
Hybrid
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Your applicationOpen nowData Engineer | Hybrid SetupHRTX

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The clock on this job

Early applications get read.

12.3% of postings close within 7 days. Measured by our own scanner across the market.

Share of postings closed within
  1. 2.1%1 day
  2. 4.5%3 days
  3. 12.3%7 days
  4. 19.3%14 days
  5. 35.6%30 days
  6. 58.1%60 days
This job: first seen 6 hours ago

The posting

Work Setup: Monday to Friday, Hybrid (2 days onsite, 3 days wfh) Location: Mandaluyong

Key Responsibilities:

  • Assist in developing and successfully deploying new data pipelines to support priority use cases and product features under senior guidance.
  • Monitor and maintain pipeline uptime, resolve routine data quality issues within target turnaround times, and escalate complex incidents as needed.
  • Respond to data requests and incidents within defined SLAs while ensuring successful workflow execution through established runbooks, tests, and deployment processes.
  • Maintain technical documentation and basic test coverage for owned pipelines while applying industry best practices in CI/CD, data quality, governance, and monitoring.
  • Collaborate cross-functionally through technical presentations and knowledge-sharing activities, while proactively communicating issues, risks, and blockers to the team.

Qualifications:

  • Bachelor’s degree in IT, Computer Science, Engineering, Math (or equivalent experience) with 2–3 years in data, analytics, or software engineering.
  • Proficient in Python (scripting and data processing libraries) and SQL (querying, filtering, aggregations, and joins).
  • Hands-on experience building ETL/ELT pipelines with relational databases, data warehouses, major cloud platforms (AWS preferred, GCP, Azure), and orchestration tools like Dagster or Airflow.
  • Familiarity with Git, Docker, dbt, Terraform (Infrastructure as Code), and schema migration tools (e.g., Alembic, Atlas).
  • Skilled in writing maintainable code, maintaining technical documentation, applying data quality/testing practices (e.g., Pandera), and demonstrating a strong eagerness to learn new technologies.
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