. Crane Worldwide Logistics .-posted 1 day ago
Full-time • Mid Level
Houston, TX
1,001-5,000 employees

ESSENTIAL JOB FUNCTIONS Architecture & Design Leadership Define platform and data architecture direction in partnership with other tech leads and senior engineers Lead and guide the engineers to do design reviews through RFCs, peer discussion, and structured technical feedback Represent the team in cross-domain technical forums (schemas, Kafka workflows, data governance, etc.) Establish repeatable patterns and engineering best practices that raise the engineering bar across the organization Backlog & Delivery Partner with engineering and product stakeholders to run backlog processes and set clear priorities Lead sprint planning, including effort estimation, team allocation, and acceptance criteria (definition of done) Facilitate daily stand-ups and drive active engagement and accountability Maintain and facilitate consistent PR review throughput and ensure healthy peer review practices Operational Excellence Own SLA-setting and reviews in collaboration with engineering management Maintain and improve runbooks, on-call documentation, and incident workflows Act as incident commander during P0/P1 events and coordinate cross-functional response Ensure post-incident reviews lead to measurable improvements in reliability and observability Technical Contribution Balance technical leadership with direct contributions to the codebase, spending meaning fulltime on hands‑on coding to remain close to implementation details. Ship critical-path features and guide others in delivering scalable, maintainable solutions Mentor engineers through pairing, code reviews, and knowledge-sharing Documentation & Knowledge Management Maintain up-to-date documentation for runbooks, RFCs, architectural decisions, and incident workflows Promote a documentation-first, async-friendly culture that supports distributed collaboration Mentorship & Coaching Mentor engineers to deliver independently by helping them break down ambiguous problems and scope work effectively Provide technical guidance and clarify project direction as needed Foster a culture of collaboration and teamwork by pairing with engineers on complex challenges and on-call issues Coach engineers on writing RFCs and presenting technical designs to broader audiences Leadership Expectations Be confident and data driven in decision-making Advocate for engineering best practices even when inconvenient Balance coding time with leadership, facilitation, and mentoring Foster a culture of clear documentation, healthy debate, and ownership Communicate proactively across teams and functions OTHER SKILLS & ABILITIES Track record of leading architectural decisions and driving technical alignment across teams Excellent communication skills with the ability to facilitate technical discussions and drive decisions Strong documentation habits and commitment to reducing tribal knowledge Data warehouses: Snowflake Observability: Prometheus, Grafana, PagerDuty, Data quality/governance experience Schema management: Schema Registry, Protobuf, Avro PREFERRED QUALIFICATIONS Languages: Python or any other higher-level programming language, proficiency in SQL Streaming: Kafka, redpanda or any other streaming service Batch: dbt or equivalent tool Cloud: AWS/GCP/Azure Databases: PostgreSQL or equivalent Infrastructure: Kubernetes, Docker, Terraform, docker CI/CD: Git, GitHub, GitHub Actions EDUCATION & EXPERIENCE Bachelor's Degree in Information Technology, Math, or related field; Equivalent experience will be considered High School Diploma or GED equivalency required 4+ years of software engineering experience in data platform and infrastructure Deep experience building and operating large-scale data platforms or distributed data systems Strong proficiency in backend languages commonly used in data engineering (e.g., Python,Java, Scala, Go) Hands-on experience with streaming technologies (Kafka, Redpanda, Materialize, or similar) and data pipeline orchestration

  • Define platform and data architecture direction
  • Lead design reviews
  • Represent the team in cross-domain technical forums
  • Establish repeatable patterns and engineering best practices
  • Partner with stakeholders to run backlog processes and set clear priorities
  • Lead sprint planning
  • Facilitate daily stand-ups
  • Maintain consistent PR review throughput
  • Own SLA-setting and reviews
  • Maintain and improve runbooks, on-call documentation, and incident workflows
  • Act as incident commander during P0/P1 events
  • Ensure post-incident reviews lead to measurable improvements
  • Balance technical leadership with direct contributions to the codebase
  • Ship critical-path features and guide others
  • Mentor engineers through pairing, code reviews, and knowledge-sharing
  • Maintain up-to-date documentation
  • Promote a documentation-first, async-friendly culture
  • Mentor engineers to deliver independently
  • Provide technical guidance and clarify project direction
  • Foster a culture of collaboration and teamwork
  • Coach engineers on writing RFCs and presenting technical designs
  • Be confident and data driven in decision-making
  • Advocate for engineering best practices
  • Balance coding time with leadership, facilitation, and mentoring
  • Foster a culture of clear documentation, healthy debate, and ownership
  • Communicate proactively across teams and functions
  • Track record of leading architectural decisions and driving technical alignment across teams
  • Excellent communication skills with the ability to facilitate technical discussions and drive decisions
  • Strong documentation habits and commitment to reducing tribal knowledge
  • Data warehouses: Snowflake
  • Observability: Prometheus, Grafana, PagerDuty
  • Data quality/governance experience
  • Schema management: Schema Registry, Protobuf, Avro
  • Bachelor's Degree in Information Technology, Math, or related field; Equivalent experience will be considered
  • High School Diploma or GED equivalency required
  • 4+ years of software engineering experience in data platform and infrastructure
  • Deep experience building and operating large-scale data platforms or distributed data systems
  • Strong proficiency in backend languages commonly used in data engineering (e.g., Python,Java, Scala, Go)
  • Hands-on experience with streaming technologies (Kafka, Redpanda, Materialize, or similar) and data pipeline orchestration
  • Languages: Python or any other higher-level programming language, proficiency in SQL
  • Streaming: Kafka, redpanda or any other streaming service
  • Batch: dbt or equivalent tool
  • Cloud: AWS/GCP/Azure
  • Databases: PostgreSQL or equivalent
  • Infrastructure: Kubernetes, Docker, Terraform, docker
  • CI/CD: Git, GitHub, GitHub Actions
  • Quarterly Incentive Plan
  • 136 hours of Paid Time Off which equals 17 days for the year, that can be used for Sick Time or for Personal Use
  • Excellent Medical, Dental and Vision benefits
  • Tuition Reimbursement for education related to your job
  • Employee Referral Bonuses
  • Employee Recognition and Rewards Program
  • Paid Volunteer Time to support a cause that is close to your heart and contributes to our communities
  • Employee Discounts
  • Wellness Incentives that can go up to $100 per year for completing challenges, in addition to a discount on contribution rates
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