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Data Engineer

Tabner IncDenver, NC🇺🇸United StatesPosted 5 Aug 2026

Why This Role Stands Out

You'll thrive as a Data Engineer at Tabner Inc. by building and operating a cutting-edge data platform using Apache Iceberg and Docker microservices, offering significant opportunities for technical growth and ownership. This hybrid role is perfect for a mid-senior engineer eager to develop expertise in modern data technologies, CI/CD, and robust system observability.

Quick Overview

Seniority
Mid Senior
Work mode
Hybrid
Location
Denver, NC, United States
Posted
3 weeks ago
DockerETLFlinkAnsibleApacheData PipelineGDPRGrafanaHIPAAHiveKafkaPrometheusPython

Job Description

Job Summary:

We are looking for a mid level engineer to build and operate a data platform that uses Apache Iceberg as the lake house table format and Docker based micro services (Spark, Flink, Presto, etc.). you will own the end to end delivery pipeline, monitoring, security, and incident response, ensuring the platform runs reliably at scale.

 

Key Responsibilities:

  • Iceberg operations: support tables, manage schema changes, partitions, snapshot retention, and keep the catalog (Hive Metastore, AWSGlue, Nessie, ) synchronized.
  • Docker image creation & testing: write multi stage Dockerfiles for Spark/Flink/Presto, run local test environments with Docker Compose, and conduct vulnerability scans (Trivy, Snyk, ).
  • Data pipeline development: build ETL/ELT jobs that ingest raw data and write to Iceberg tables; add simple streaming components using Kafka, Pulsar, or Kinesis when needed.
  • CI/CD automation: configure pipelines (GitHubActions, GitLabCI, AzureDevOps, ) to lint Dockerfiles, scan images, version Iceberg metadata, and deploy pipelines without downtime.
  • Automation with Ansible/Python: script cluster provisioning, catalog configuration, vacuum/compaction, and other routine housekeeping tasks.
  • Observability: instrument services with OpenTelemetry, Prometheus, Grafana, and Loki; create dashboards showing pipeline latency, resource usage, table health, and error rates; set up basic alerts.
  • SLA monitoring: measure data freshness, job success rates, and query response times against agreed upon targets and report deviations.
  • Incident response: join the on call rotation, perform first line diagnosis and resolution of pipeline failures, Iceberg metadata issues, or container crashes; write concise root cause analyses and suggest improvements.
  • Security & compliance support: help enforce image signing, mTLS, IAM roles, and bucket policies; collaborate with the security team to meet GDPR, HIPAA, or ISO27001 requirements.
  • Knowledge sharing: keep internal documentation up to date and run short tech demos or brown bag sessions on Iceberg, Docker best practices, and automation techniques.

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