Assistant Manager - Data Engineering
Posted
Summary
Lead Data Engineer role at Latent View Analytics in Negros Occidental, Philippines: build, deploy, and own ETL/ELT pipelines across on-prem and cloud (GCP), drive technical decisions, review code, and mentor other data engineers. Core stack: PostgreSQL, BigQuery, Spark, Kubernetes, Jenkins, Python, and SQL.
We're hiring a Lead Data Engineer to build and deploy data pipelines across on-prem and cloud environments. You should be comfortable in PostgreSQL, GCP/BigQuery, Spark, Kubernetes, and Jenkins, and ready to take ownership of how pipelines get architected and deployed.
As the lead on this, you'll drive technical decisions, review other engineers' work, and be the go-to person when something in the pipeline needs fixing or rethinking.
Key Responsibilities
- Build and maintain ETL/ELT pipelines end to end
- Set up and manage Jenkins pipelines for deployment and job orchestration
- Write and optimize PostgreSQL queries and schemas
- Build data solutions on GCP, including BigQuery
- Write Spark jobs for distributed data processing
- Deploy and manage containerized workloads on Kubernetes
- Keep pipelines monitored and reliable - handle errors, logging, and recovery properly
- Write clean, tested Python and SQL
- Review code and keep the team's CI/CD and version control practices solid
- Mentor other data engineers on the team
Required Qualifications
- 5+ years of hands-on data engineering experience, with real ownership of production pipelines (not just contributing to them)
- Strong experience with GCP, including big data ETL and containerized ETL workloads
- Proficiency with Apache Spark for distributed/batch processing
- Experience with Kubernetes for container orchestration
- Solid track record building and managing Jenkins pipelines
- Strong PostgreSQL skills, including query optimization and schema design in an on-prem setting
- Experience running ETL workflows in on-prem environments, not just cloud-native setups
- Strong SQL and Python skills
- Experience building ETL/ELT pipelines from raw source data through to modeling-ready datasets
Preferred Qualifications
- Experience with hybrid architecture - moving and syncing data between on-prem and cloud
- Familiarity with dimensional data modeling for analytics/BI (star schema, etc.)
- Experience with infrastructure-as-code (Terraform, Helm) for Kubernetes/GCP
- Familiarity with data quality/testing tools like Great Expectations or dbt tests
- Experience mentoring or leading other data engineers
