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Live, first seen by us 25 days agoEmployment type in the employer’s posting: Full timeFrom the employer’s posting
Design and maintain analytical data models and transformations over BigQuery and ClickHouse
Define and standardize core energy, equipment and platform metrics with clear documentation
Build and operate tested ELT pipelines with version control, code review and CI/CD
Optimize query performance and storage cost on large time-series datasets
Turn ambiguous questions from product and customer teams into datasets and dashboards
Design, build and maintain the analytical data models and transformation layer over our warehouse and analytical stores (BigQuery, ClickHouse)
Define and standardize core business and product metrics, energy consumption, equipment performance, portfolio benchmarks, platform usage, with clear ownership, lineage and documentation.
Build and operate reliable, tested ELT pipelines with software engineering discipline: version control, code review, CI/CD, data quality checks and alerting.
Optimize query performance and storage cost across large time-series datasets, including schema design, partitioning and materialized views.
Partner with product managers, backend engineers and customer success to translate ambiguous questions into datasets, dashboards and self-serve analytics.
5+ years of experience in analytics engineering, data engineering or a closely related role, with at least 2 years owning data models used in production by other teams.
Experience with time-series data, IoT telemetry, or the built environment (BMS/BAS, energy metering, sustainability reporting frameworks
Hands-on experience with a cloud data warehouse, ideally BigQuery on Google Cloud, and with columnar/OLAP databases such as ClickHouse.
Familiarity with orchestration tools (Airflow, Dagster or similar) and infrastructure-as-code on GCP.
Experience working with streaming or high-volume event data (e.g. Kafka) and document stores (e.g. MongoDB) as upstream sources.
Strong communication skills in English and the ability to work autonomously in a remote, cross-timezone team.
From the employer’s posting.
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Day 25
Similar jobs usually come down between day 6 and day 47.
From 1,405 similar postings that came down. Coming down is not always a hire.
6 open jobs
Open jobs by the week we first saw them, last 12 weeks.
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- Hands-on experience with a cloud data warehouse, ideally BigQuery on Google Cloud, and with columnar/OLAP databases such as ClickHouse. - Solid programming skills in Python (or a comparable language) for pipeline development and automation. - Experience working with streaming or high-volume event data (e.g. Kafka) and document stores (e.g. MongoDB) as upstream sources.
- 5+ years of experience in analytics engineering, data engineering or a closely related role, with at least 2 years owning data models used in production by other teams. - Expert-level SQL and strong experience with a modern transformation framework (dbt or equivalent), including testing, documentation and CI. - Hands-on experience with a cloud data warehouse, ideally BigQuery on Google Cloud, and with columnar/OLAP databases such as ClickHouse.
WHAT YOU WILL DO: - Design, build and maintain the analytical data models and transformation layer over our warehouse and analytical stores (BigQuery, ClickHouse), turning high-volume building telemetry into clean, documented, query-ready datasets. - Define and standardize core business and product metrics, energy consumption, equipment performance, portfolio benchmarks, platform usage, with clear ownership, lineage and documentation.
- Expert-level SQL and strong experience with a modern transformation framework (dbt or equivalent), including testing, documentation and CI. - Hands-on experience with a cloud data warehouse, ideally BigQuery on Google Cloud, and with columnar/OLAP databases such as ClickHouse. - Solid programming skills in Python (or a comparable language) for pipeline development and automation.
Buildings generate an enormous amount of telemetry, sensor readings, equipment states, energy meters, alarms, flowing through our platform every second. In this role, you will own the layer that turns this raw data into trusted, well-modeled datasets that power customer-facing analytics, energy and sustainability reporting, internal decision-making and the features our product teams build on top of the data. You will work at the intersection of data engineering, analytics and product: designing data models over our GCP and ClickHouse stack, building reliable transformation pipelines, defining metrics that the whole company can trust, and partnering with product, engineering and customer teams to make data a first-class product. WHAT YOU WILL DO:
- Solid programming skills in Python (or a comparable language) for pipeline development and automation. - Experience working with streaming or high-volume event data (e.g. Kafka) and document stores (e.g. MongoDB) as upstream sources. - A track record of defining metrics and building semantic layers or BI models that non-technical stakeholders rely on daily.
- Experience with time-series data, IoT telemetry, or the built environment (BMS/BAS, energy metering, sustainability reporting frameworks - Familiarity with orchestration tools (Airflow, Dagster or similar) and infrastructure-as-code on GCP. - Exposure to data governance, cataloging and privacy practices in a B2B SaaS environment.
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We file this job under Analytics Engineer, by the work the posting describes.
Analytics engineers turn raw warehouse data into clean, tested and documented tables that analysts and dashboards can rely on, often with dbt.
Expect strong SQL, data modeling, Git, and a warehouse such as Snowflake, BigQuery or Redshift.
A data engineer gets data into the warehouse; an analytics engineer shapes it once it is there and works closer to the analysts who use it.
The government has no code for analytics engineers, so these figures are for the closest group, database architects, the same group we use for data engineers.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.
KODE Labs, headquartered in Detroit, Michigan, is seeking a Senior Analytics Engineer to join our growing team.
Buildings generate an enormous amount of telemetry, sensor readings, equipment states, energy meters, alarms, flowing through our platform every second. In this role, you will own the layer that turns this raw data into trusted, well-modeled datasets that power customer-facing analytics, energy and sustainability reporting, internal decision-making and the features our product teams build on top of the data.
You will work at the intersection of data engineering, analytics and product: designing data models over our GCP and ClickHouse stack, building reliable transformation pipelines, defining metrics that the whole company can trust, and partnering with product, engineering and customer teams to make data a first-class product.
WHAT YOU WILL DO:
Design, build and maintain the analytical data models and transformation layer over our warehouse and analytical stores (BigQuery, ClickHouse), turning high-volume building telemetry into clean, documented, query-ready datasets.
Define and standardize core business and product metrics, energy consumption, equipment performance, portfolio benchmarks, platform usage, with clear ownership, lineage and documentation.
Build and operate reliable, tested ELT pipelines with software engineering discipline: version control, code review, CI/CD, data quality checks and alerting.
Optimize query performance and storage cost across large time-series datasets, including schema design, partitioning and materialized views.
Partner with product managers, backend engineers and customer success to translate ambiguous questions into datasets, dashboards and self-serve analytics.
Support customer-facing reporting on energy, sustainability and building performance, where the numbers we publish must stand up to scrutiny.
Mentor other engineers and analysts, set standards for analytics engineering practice, and help shape the roadmap of our data platform.
5+ years of experience in analytics engineering, data engineering or a closely related role, with at least 2 years owning data models used in production by other teams.
Expert-level SQL and strong experience with a modern transformation framework (dbt or equivalent), including testing, documentation and CI.
Hands-on experience with a cloud data warehouse, ideally BigQuery on Google Cloud, and with columnar/OLAP databases such as ClickHouse.
Solid programming skills in Python (or a comparable language) for pipeline development and automation.
Experience working with streaming or high-volume event data (e.g. Kafka) and document stores (e.g. MongoDB) as upstream sources.
A track record of defining metrics and building semantic layers or BI models that non-technical stakeholders rely on daily.
Strong communication skills in English and the ability to work autonomously in a remote, cross-timezone team.
WHAT GIVES YOU AN EDGE:
Experience with time-series data, IoT telemetry, or the built environment (BMS/BAS, energy metering, sustainability reporting frameworks
Familiarity with orchestration tools (Airflow, Dagster or similar) and infrastructure-as-code on GCP.
Exposure to data governance, cataloging and privacy practices in a B2B SaaS environment.
Competitive salary based on experience
Discretionary Bonus Program
Career Development Program and opportunities to grow within the company
Flexible Paid Time Off
Comprehensive Health Insurance Package
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.
If KODE Labs sounds like the place for you, we’d love to hear your story, so please apply through our online application form. Only shortlisted candidates will be contacted.
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- A track record of defining metrics and building semantic layers or BI models that non-technical stakeholders rely on daily. - Strong communication skills in English and the ability to work autonomously in a remote, cross-timezone team. WHAT GIVES YOU AN EDGE:
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