Staff Data Engineer: Core Data Pipelines & Observability

KODE Labs

Detroit (MI)

On-site

USD 140,000 - 190,000

Full time

14 days+
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Benefits offered by this job

Competitive salary
Discretionary bonus
Career development
Flexible PTO
Dynamic team
Onboarding program
Friendly work environment
Social events

Job summary

KODE Labs in Detroit, MI is seeking a Staff Data Engineer to lead the technical foundations of our data pipelines, data alignment, quality, and observability. You will design and evolve core data pipelines and datasets that serve as shared foundations across KODE OS, with emphasis on IoT, time-series, and Digital Twin integration across multiple teams.

This role combines hands-on engineering with technical leadership, mentoring others and establishing standards for data contracts, lineage, and

Qualifications

  • Staff-level experience in data engineering or data platform engineering.
  • Strong proficiency in SQL and Python.
  • Experience with IoT, telemetry, time-series, or high-volume event data.
  • Experience with Digital Twins, ontologies, or semantic data models.
  • Hands-on experience with Kafka, Flink, Spark, Airflow, dbt, BigQuery, ClickHouse, PostgreSQL.

Responsibilities

  • Design, build, and evolve core data pipelines and datasets that serve as shared foundations across KODE OS.
  • Define reusable patterns for aligning IoT, data sources with Digital Twin.
  • Establish standards for the full data lifecycle from ingestion to consumption.
  • Build shared frameworks for data validation, normalization, lineage, observability, and readiness.
  • Define data quality approaches including flags, confidence scores, validation signals, and product-readiness checks.
  • Establish time-series standards covering timestamps, time zones, frequencies, gaps, late-arriving data, duplicates, and aggregation grains.
  • Define and evolve data contracts, schema standards, and versioning across producers and consumers.
  • Build observability foundations to surface issues before they affect downstream products.
  • Develop reusable mapping and alignment patterns for onboarding new integrations and data sources.
  • Partner with Integrations and Digital Twin engineers to ensure identifiers and metadata are reliable.
  • Work with FDD, Energy, Analytics, API, and AI teams to ensure data quality and readiness signals.
  • Review new data models and cross-team data flows to follow shared standards.
  • Provide technical leadership and mentor engineers across teams.

Skills

SQL
Python
Kafka
Flink
Spark
Airflow
dbt
BigQuery
ClickHouse
PostgreSQL
Time-series data
IoT data
Data modeling
Observability
Data quality
Schema evolution
Mentoring

Tools

Kafka
Flink
Spark
Airflow
dbt
BigQuery
ClickHouse
PostgreSQL

Job description

KODE Labs in Detroit, MI is seeking a Staff Data Engineer to lead the technical foundations of our data pipelines, data alignment, quality, and observability. You will design and evolve core data pipelines and datasets that serve as shared foundations across KODE OS, with emphasis on IoT, time-series, and Digital Twin integration across multiple teams.

This role combines hands-on engineering with technical leadership, mentoring others and establishing standards for data contracts, lineage, and

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