1 day ago
Remote, Mexico +2 moreMid Level / Senior
H1B sponsor
Responsibilities
- Own day-to-day engineering of the governed data platform, including model changes, backlog work, data-source onboarding, CI/CD maintenance, and infrastructure operations.
- Build, test, and maintain data models and pipelines supporting dashboards, finance and investor reporting, and AI analytics across 15+ business domains.
- Provision and configure BigQuery datasets, views, GCS buckets, and IAM permissions through Terraform, including access controls and schema-drift handling.
- Extend RBAC, maintain data catalog metadata and documentation, and support data access governance.
- Improve platform reliability through stronger testing standards, observability, and alerting.
- Support Airflow and dbt orchestration, scheduling, and troubleshooting in Cloud Composer.
- Build and maintain Python-based Fivetran SDK connectors with pagination, rate limiting, error handling, and automated tests.
- Partner with BI analysts and business stakeholders to create well-modeled, trustworthy datasets and improve engineering practices through code review and shared standards.
- Use AI coding tools to accelerate routine development work.
Requirements
- 3–5 years of experience in analytics engineering, data engineering, or BI engineering.
- Strong SQL skills and experience designing, optimizing, and maintaining layered analytical data models.
- Professional experience building and maintaining dbt projects, including packages, macros, incremental strategies, snapshots, seeds, deferred builds, state comparison, and slim CI.
- Experience with version control, code review, automated testing, and CI/CD for data projects.
- Ability to debug data issues and reason about freshness, volume, duplicates, and late-arriving data.
- Ability to translate business needs into data requirements and collaborate with non-technical stakeholders, including Finance.
- Comfort working across multiple repositories covering transformation, infrastructure, orchestration, connectors, and cloud resources.
- Demonstrated use of AI coding tools in a daily workflow.
- Ability to work independently in a remote global team with strong written communication and documentation habits.
- Fluent written and spoken English; additional languages are advantageous.
- Preferred experience with BigQuery, Fivetran, Apache Airflow, Cloud Composer, or equivalent AWS/Azure technologies.
- Preferred experience with data catalogs such as OpenMetadata or observability tools such as Elementary.
- Preferred experience with branch-based CI/CD, slim CI, Docker image builds, and automated plan/apply workflows.
- Preferred experience provisioning BigQuery datasets, IAM bindings, or GCS buckets with Terraform.
- Preferred experience writing Python integrations for REST APIs, including pagination, rate limiting, and error handling.
- Preferred understanding of dbt compilation, Jinja, SQL execution phases, snapshots, and advanced macros.
- Preferred experience tuning BigQuery through partitioning, clustering, incremental strategies, and slot and query-cost analysis.
- Preferred experience with Docker, Kubernetes, and GKE for debugging containerized dbt builds.
- Preferred experience with SQLFluff, pre-commit frameworks, or custom validation scripts.
- Preferred familiarity with CRM, support, project management, marketing automation, or ERP source systems.
Benefits
- Remote work with flexible working options and schedules that meaningfully overlap with US time zones.
- The role is full-time employment in Mexico or Colombia, or a contractor position in other LATAM locations.
- Unlimited vacation.
- Health insurance.
- Parental leave.
- Employee stock option plan.
- Home office allowance.
- Professional development stipend.
- Peer recognition program.
Categories
Data Engineering
About DoiT
DoiT builds a multicloud management and FinOps platform, combined with embedded cloud engineering services, for companies running on AWS, Google Cloud, and Azure. It helps customers optimize costs, simplify billing, and improve architectures across Kubernetes, BigQuery, Snowflake, and Databricks. Founded in 2011 and headquartered in Santa Clara, it is a privately held cloud partner with a $100M Series A raised in 2019.