DataOps Engineer

SBT Global, Inc.

$122K *
Enterprise Technology
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • Bachelor's degree in Computer Science, IT, Data Engineering or related field (Master's preferred)
  • 5 years of experience with large-scale data platform operations
  • Proven experience with Apache Iceberg and its operational aspects
  • Strong Docker skills for image creation and testing
  • Knowledge of data-processing engines like Spark, Flink, or Presto
  • Proficient in Python and/or Ansible for automation
  • Experience with CI/CD pipeline automation involving Docker and data-pipeline code

Responsibilities

  • Support Iceberg operations including schema management and catalog synchronization
  • Create and test Docker images using multi-stage builds and conduct security scans
  • Develop ETL/ELT jobs for data ingestion into Iceberg tables
  • Automate CI/CD pipelines with tools like GitHub Actions and Azure DevOps
  • Script routine tasks for cluster provisioning and catalog management using Ansible/Python
  • Instrument services with observability tools and create dashboards
  • Monitor SLA metrics and respond to incidents as part of an on-call rotation

Benefits

  • Relocation support to Plano, TX post-2026
  • Engagement in knowledge-sharing through tech demos and documentation updates
  • Opportunities to work with cutting-edge technologies in data engineering
  • Participation in incident response and learning from real-world problems
Full Job Description
1 yr Contract Full-Time, On Site Relocation Required (Englewood Cliffs, NJ until 9/2026, Plano, TX effective 10/2026) Pay Rate: ~$10,190/mo DOE 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. Job Description 3Iceberg operations: support tables, manage schema changes, partitions, snapshot retention, and keep the catalog (Hive Metastore, AWS Glue, Nessie, ...) synchronized. 3Docker image creation & testing: write multi-stage Dockerfiles for Spark/Flink/Presto, run local test environments with Docker-Compose, and conduct vulnerability scans (Trivy, Snyk, ...). 3Data 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. 3CI/CD automation: configure pipelines (GitHub Actions, GitLab CI, Azure DevOps, ...) to lint Dockerfiles, scan images, version Iceberg metadata, and deploy pipelines without downtime. 3Automation with Ansible/Python: script cluster provisioning, catalog configuration, vacuum/compaction, and other routine housekeeping tasks. 3Observability: instrument services with OpenTelemetry, Prometheus, Grafana, and Loki; create dashboards showing pipeline latency, resource usage, table health, and error rates; set up basic alerts. 3SLA monitoring: measure data freshness, job success rates, and query response times against agreed-upon targets and report deviations. 3Incident 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. 3Security & compliance support: help enforce image signing, mTLS, IAM roles, and bucket policies; collaborate with the security team to meet GDPR, HIPAA, or ISO 27001 requirements. 3Knowledge sharing: keep internal documentation up to date and run short tech demos or brown-bag sessions on Iceberg, Docker best practices, and automation techniques. Qualifications Requirements 3Bachelor's degree in Computer Science, IT, Data Engineering, or a related field (Master's a plus). 3~5 years of hands-on experience building and operating large-scale data platforms (lake-house, data-warehouse, or big-data ecosystems). 3Proven production experience with Apache Iceberg (table creation, partition management, schema evolution, catalog integration). 3Strong Docker skills: multi-stage builds, Docker-Compose testing, routine image security scanning. 3Experience with at least one major data-processing engine (Spark, Flink, or Presto/Trino) and its connection to Iceberg tables. 3Proficiency in Python and/or Ansible for automating infrastructure and platform tasks. 3Experience building CI/CD pipelines that include Docker linting, vulnerability scanning, and automated deployment of data-pipeline code. 3Familiarity with observability tooling (Prometheus, Grafana, OpenTelemetry, Loki) and ability to create useful alerts and dashboards. 3Ability to respond to incidents, write clear root-cause analysis reports, and contribute to post-mortem actions. 3Willingness to participate in an on-call rotation as a first-line responder. 3Availability to work on-site in New Jersey for the initial assignment and relocate to Dallas by October 2026. Preferred Qualifications 3Experience with cloud-native data services on AWS, Azure, or GCP (EMR, Dataproc, Synapse, etc.). 3Familiarity with other lake-house formats such as Delta Lake or Apache Hudi and ability to evaluate trade-offs against Iceberg. 3Knowledge of streaming platforms (Kafka, Pulsar, Kinesis) and real-time processing patterns. 3Relevant certifications (Databricks Lakehouse Associate, Google Professional Data Engineer, AWS Certified Data Analytics - Specialty, etc.). 3Background supporting data platforms in regulated industries (pharma, finance, healthcare) and understanding of associated compliance frameworks. Additional Information

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