Data Engineer Infra / DataOps Engineer
Guinea MobileCiudad de México, Ciudad de México, MexicoHace 10 días
Descripción del trabajoCore GCP data processing : batch / stream in Dataflow, BigQuery Streaming, partitioning, windows, backfills. Infra / DataOps : Pub / Sub, Dataflow or Dataproc (Spark), Cloud Composer orchestration. BI : analytical dataset preparation in BigQuery, aggregations, metrics and SCD with dbt. Databases and storage : BigQuery DWH; Cloud Storage for data lake; Cloud SQL PostgreSQL when applicable; design partitioning / clustering, external tables in GCS, Bigtable for time‑series. ETL / ELT : dbt (BigQuery) models, tests and documentation; Cloud Composer dependencies; pipelines with Dataflow, backfills, Great Expectations. Programming : Python for data (pandas / pyarrow), CLI, testing; containerized jobs (Docker), Beam / Spark performance and parallelism. Cloud computing : IAM, service accounts, BigQuery cost control; Cloud Build CI; Terraform IaC; Cloud Monitoring / Logging; lineage / catalog with Dataplex / Data Catalog. Data quality and security : validation, profiling, documentation; SLO / SLA alerts, drift / duplicates detection, DLP, KMS, VPC‑SC. Query optimization : BigQuery tuning, partitioning / clustering, Reservations / slots, Storage API. BI : design of facts / dimensions, BI Engine. Mindset SRE / automation : everything as code, resilience and recovery. Obsessed with observability : logs, metrics, tracing and actionable lineage. Affinity with performance / costs : tuning of slots, partitioning, throughput. Rigor in security / governance : least privilege, audit, compliance. Clear technical communication : runbooks, postmortems and interface design between teams.
Company Overview
Guinea Mobile SAC is a Latin American telecom technology startup founded in 2016 in Lima, Peru, creating mobile products.
Base Pay Range
Pay will be based on skills and experience – discuss with recruiter.
Responsibilities
- Design Pub / Sub → Dataflow → BigQuery pipelines with SLA / SLO and end‑to‑end observability.
- Implement data CI / CD (Cloud Build / Deploy), IaC with Terraform and reproducible environments.
- Manage evolving schema, data contracts and secure backfills.
- Optimize BigQuery costs and performance (partitioning, clustering, slots, materializations).
- Automate data quality (dbt tests / Great Expectations) with alerts on Cloud Monitoring.
- Ensure governance and security (domain permissions, DLP / KMS, audit, VPC‑SC when applicable).
Qualifications
Preferred Profile
Employment Details
Full‑time, Information Technology. Industries : Technology, Information and Internet and Information Technology & Services.
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Data Engineer • Ciudad de México, Ciudad de México, Mexico
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