Data Infrastructure Engineer (Batch / Lake / Streaming) - LA- Remote: Colombia - Costa Rica, Fulltime.

- This position is open to candidates located in Colombia or Costa Rica only -

About the role

We are looking for Data Infrastructure Engineers to work on large-scale data platforms for one of our enterprise clients. Depending on your background and interests, you may focus on Batch Infrastructure, Data Lake / Lakehouse Infrastructure, or Streaming Infrastructure.
This role is ideal for engineers who enjoy operating and evolving data platforms in production, improving reliability, automation, and performance across distributed systems.

What You’ll Do

Operate and support production-grade data infrastructure across batch, lakehouse, or streaming environments

Improve reliability through automation, monitoring, observability, and incident response

Build, maintain, and optimize data pipelines and platform tooling

Support upgrades, migrations, and platform evolution initiatives

Collaborate closely with data engineers, analytics teams, and platform stakeholders

Handle KTLO work, including maintenance, troubleshooting, and documentation

Apply infrastructure best practices using cloud-native and IaC approaches

Role Variants
Depending on your experience, you may work primarily in one of these areas:

Batch Infrastructure

Workflow orchestration and scheduling

Batch pipelines and dependency management

Tools such as Airflow, Luigi, Temporal, Dagster

Python-based automation and platform tooling

Lake / Lakehouse Infrastructure

Data lake and lakehouse platforms

Distributed processing with Spark / Databricks

Technologies such as Iceberg, Delta Lake, Snowflake, BigQuery

Performance tuning, governance, and data reliability

Streaming Infrastructure

Real-time or near-real-time data pipelines

Event-driven architectures and streaming systems

Technologies such as Kafka, Flink, Spark Streaming, Kinesis

Low-latency processing and streaming observability

Required Qualifications

Strong experience with Python or Java

Hands-on experience operating distributed systems in production

Experience working with cloud platforms (AWS, GCP, or Azure)

Familiarity with data infrastructure or data platform concepts

Comfortable working on reliability, maintenance, and operational tasks

Ability to collaborate with cross-functional and client-facing teams

Advanced English level to work directly with clients

Nice to Have

Experience with orchestration tools (Airflow, Dagster, Temporal, Luigi)

Experience with Spark, Databricks, or lakehouse technologies

Experience with Kafka, Flink, or streaming platforms

Infrastructure as Code (Terraform, CloudFormation)

Kubernetes and containerized workloads

Observability tooling (Prometheus, Grafana, Datadog, etc.)