Data Engineer

Kpler

. Design, implement, and operate flexible data ingestion frameworks using Java and Python with Kafka, S3, Iceberg, and Airflow .

Posted 9/15/2026full-timeColombiaMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Proficient in designing and implementing data ingestion frameworks using Java and Python, with a strong focus on performance tuning and observability in cloud environments. Demonstrates ownership of production data pipelines and collaborates effectively with cross-functional teams to optimize data workflows.

Highest-signal resume keywords

Java ProgrammingPython ProgrammingKafka Data IngestionSnowflake AnalyticsAWS Cloud Services

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data EngineeringSQLData ModelingKubernetes DeploymentPerformance Tuning

Soft Skills

Strong Communication

Tools & Technologies

AirflowS3IcebergClickHouseGitOps

Industry Keywords

Data Ingestion PipelinesCloud Data WarehouseMonitoring and ObservabilityOLAP EnginesCross-Functional Collaboration

Tech Stack

Tools & technologies

AirflowAWSCloudJavaJavaScriptKafkaKubernetesPythonSQLTypeScriptVue.js

About the role

Key responsibilities & impact

Design, implement, and operate flexible data ingestion frameworks using Java and Python with Kafka, S3, Iceberg, and Airflow
Power analytical platforms including Snowflake and ClickHouse
Maintain end-to-end service ownership through proactive monitoring, actionable alerts, pipeline failure reduction, and on-call readiness
Break down complex engineering problems, author design proposals, and lead peer engineers to deliver technical projects
Build reusable tools, documentation, and paved paths for engineering teams adopting data ingestion frameworks
Collaborate with Cloud Platform engineers, Product Managers, tech leads, and client technical teams
Onboard engineers, conduct code reviews, and share technical best practices
Ensure reliability, performance, and observability of scalable data flows across Kpler’s product ecosystem

Requirements

What you’ll need

~3+ years of professional software or data engineering experience building, operating, and maintaining production data ingestion pipelines (batch/streaming) using tools like Kafka, S3, Iceberg, or Airflow
High proficiency in Java and Python
Strong SQL skills
Data modeling fundamentals
Analytical warehouse experience with Snowflake or equivalent cloud data warehouse
Demonstrated ownership of production cloud services on AWS
Experience with monitoring/observability and performance tuning
Kubernetes deployment workflows (GitOps/CI/CD)
Strong communication skills to partner with cross-functional product, platform, and external client technical teams
Hands-on experience optimizing Snowflake resource sizing and cost/performance trade-offs, or operating OLAP engines like ClickHouse (nice-to-have)
Familiarity with AWS Transfer Family (sFTP), Excel add-in integrations, or Python boto3 client data delivery setups (nice-to-have)
Basic exposure to TypeScript, Vue.js, or API integrations (nice-to-have)

Benefits

Comp & perks

Full-time employment
Equal opportunity employer
Fair, inclusive and diverse work environment