Staff Data Engineer - Core Data Pipelines

KODE Labs; Detroit (MI); On-site; USD 140,000 - 190,000; Full time

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

Our team at KODE Labs is looking for a Staff Data Engineer to lead the technical foundations behind our core data pipelines, data alignment, quality, lineage, and observability standards.

This is a highly cross-functional technical leadership role. You’ll build shared data foundations while defining the patterns and standards used by teams across Integrations, Digital Twin, Data Platform, Fault Detection & Diagnostics (FDD), Energy, Analytics, APIs, and AI Agents.

You won’t own every product-specific pipeline or validation rule. Instead, you’ll establish the foundations that allow teams across KODE to build on trusted, scalable, observable, and consistently modeled data.

What You Will Do

Design, build, and evolve core data pipelines and datasets that serve as shared foundations across KODE OS.

Define reusable patterns for aligning IoT, BMS, operational, asset, meter, work order, schedule, weather, occupancy, and time-series data with our Digital Twin.

Establish standards for the full data lifecycle — from raw ingestion through alignment, cleaning, modeling, serving, and consumption.

Build shared frameworks for data validation, normalization, lineage, observability, and readiness .

Define common approaches to data quality, including quality flags, confidence scores, validation signals, and product-readiness checks.

Establish time-series standards covering timestamps, time zones, expected frequencies, gaps, late-arriving data, duplicates, and standard aggregation grains.

Define and evolve data contracts, schema standards, and versioning practices across data producers and consumers.

Build observability foundations that surface issues with freshness, coverage, schema changes, data quality, pipeline failures, and data drift before they impact downstream products.

Develop reusable mapping and alignment patterns that make onboarding new integrations and data sources more consistent and scalable.

Partner closely with Integrations and Digital Twin engineers to ensure required identifiers, metadata, entity relationships, point classifications, and semantic alignment are reliable.

Work with FDD, Energy, Analytics, API, and AI teams to ensure downstream products consume data with clear quality, freshness, lineage, semantic context, and readiness indicators.

Review new data models, schemas, pipelines, mappings, and cross-team data flows to ensure they follow shared engineering standards.

Provide technical leadership across teams, helping engineers make strong architectural decisions and avoid solving the same data problems in different ways.

Mentor engineers and raise the bar for data engineering practices, system design, documentation, reliability, and maintainability across KODE.

Requirements

• Staff-level experience in data engineering or data platform engineering, with a track record of designing scalable systems and leading technical initiatives across teams.

Strong experience building and operating core data pipelines, including batch and/or streaming architectures.

Deep understanding of data modeling, data quality, contracts, lineage, observability, and schema evolution.

Strong proficiency in SQL and Python.

Experience working with IoT, telemetry, time-series, operational, or other high-volume event data.

Experience with Digital Twins, ontologies, semantic models, metadata modeling, or domain-driven data structures.

Hands‑on experience with technologies such as Kafka, Flink, Spark, Airflow, dbt, BigQuery, ClickHouse, PostgreSQL, or comparable tools.

Strong systems thinking, with the ability to design data flows from ingestion and alignment through modeling and downstream consumption.

Proven ability to set technical standards, influence architecture across teams, and mentor engineers without directly owning every implementation.

WHAT WE OFFER:

Competitive salary based on experience

Discretionary Bonus Program

Career Development Program and opportunities to grow within the company

Flexible Paid Time Off

Dynamic team and challenging projects

Custom‑tailored onboarding experience

Welcoming and friendly work environment

Social events and team activities

JOIN THE TEAM

KODE Labs is a real estate technology company founded in 2017 with a mission to change the way people, buildings, and systems operate. Headquartered in Detroit, Michigan, we are a driving force behind the adoption of smart building technology. To scale our presence across numerous cities and countries, we depend on our team of talented, ambitious people who go above and beyond to create value for our clients.

When you join the KODE Labs team you can create your own career. Whether you have years of experience or are just starting, we help you realize your full potential and achieve your goals.