Hadrian

Data Platform Engineer

Hadrian$170K — $300K *
Information Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 5-7 years of experience in production data infrastructure or distributed systems
  • Strong proficiency in Python and SQL, with data modeling expertise
  • Familiarity with event-streaming platforms like Kafka
  • Experience operating Snowflake or lakehouse architectures
  • Skilled in using orchestration tools such as Dagster or Airflow
  • Judgment in assessing data contracts and systems for analytics

Responsibilities

  • Build the foundational data backbone for autonomous factories
  • Develop ingestion, CDC, and streaming capabilities for diverse data
  • Define and manage versioned data contracts with upstream teams
  • Model operational datasets with detailed characteristics
  • Oversee orchestration and transformation processes using Dagster and dbt
  • Collaborate with teams to collect data from industrial machines and systems

Benefits

  • Comprehensive medical, dental, vision, and life insurance
  • 401k retirement plan
  • Relocation support based on business needs
  • Flexible vacation and leave policies
  • Equity options for employees
Full Job Description
The Role

Hadrian's factory data originates from production applications, operational databases, quality systems, ERP systems, and machines on the factory floor. This data fuels production schedules, machine-learning systems, engineering analysis, and company reporting.

As a Data Platform Engineer, you will own key segments of the data flow from source to trusted dataset: ingestion, change data capture, streaming, lakehouse storage, orchestration, transformation, contracts, quality, and lineage. Some data sources may involve machines, PLCs, historians, and industrial protocols. Controls experience is advantageous but not required.

This is a data-platform and distributed-systems role. Your work should enable new sources to be integrated easily, make failures straightforward to repair, and ensure datasets are reliable for use by Analytics, Data Science, Operations Research, and ML systems.

What You'll Do
  • Build the data backbone for autonomous factories, transforming machine signals, quality events, work orders, and application changes into trusted data used by scheduling, ML, and operations.
  • Build ingestion, CDC, and streaming capabilities for transactional data, events, telemetry, and files; explicitly manage ordering, deletes, retries, replay, idempotence, and backpressure.
  • Define versioned data and event contracts with upstream teams, supported by testing and service targets for freshness, completeness, and correctness.
  • Model telemetry, quality events, work orders, and operational data into datasets with explicit grain, identity, time, provenance, and history.
  • Own Dagster orchestration, dbt transformation, data CI/CD, backfills, lineage, observability, and offline feature datasets for ML.
  • Collaborate with Manufacturing Operations and Infrastructure to acquire data from machines, PLCs, historians, OPC-UA, MTConnect, and MQTT sources as needed.


What We're Looking For
  • Experience building and operating production data infrastructure or distributed data systems, including on-call ownership and recovery efforts.
  • Strong production Python and advanced SQL and data-modeling skills, including incremental processing, temporal data, and schema evolution.
  • Experience with Kafka or another event-streaming platform, plus CDC or other stateful incremental pipelines.
  • Experience operating Snowflake, and with a lakehouse table format such as Iceberg, Delta, or Hudi, including expertise in partitioning and compaction.
  • Experience with tools such as Dagster, Airflow, Argo, or Prefect; dbt or similar transformation frameworks; and Kubernetes or infrastructure as code.
  • Strong judgment regarding contracts, failure modes, and the needs of downstream analytics, ML, and operational systems.


What Will Set You Apart
  • Experience running Snowflake and Iceberg together or designing a hybrid warehouse and lakehouse architecture.
  • Production experience with PeerDB, Debezium, Flink, Spark Structured Streaming, Redpanda, Bufstream, or similar CDC and streaming systems.
  • Proficiency with ClickHouse or another low-latency analytical database, including performance tuning and lifecycle management.
  • Experience with industrial or edge data collection using OPC-UA, MTConnect, MQTT, historians, PLCs, or handling intermittently connected systems.
  • Background in performance-sensitive data systems built with Go, Rust, or Scala; regulated-environment experience; or contributions to dbt, Dagster, Iceberg, or related projects.


Compensation

$170,000 - $300,000

This represents the lowest to highest salary we reasonably and in good faith expect to pay for this role at the time of posting. Actual compensation may fall within or outside this range and the range may be updated in the future. An employee's position within the range will be determined by several factors, including relevant education, qualifications, certifications, experience, skills, geographic location, performance, and organizational needs.
Benefits for Full-time Employees
  • Medical, dental, vision, and life insurance plans for employees
  • 401k
  • Relocation support may be provided for certain situations, based on business need.
  • Flexible vacation policy
  • Equity
ITAR Requirements

To conform to U.S. Government space technology export regulations, including the International Traffic in Arms Regulations (ITAR) you must be a U.S. citizen, lawful permanent resident of the U.S., protected individual as defined by 8 U.S.C. 1324b(a)(3), or eligible to obtain the required authorizations from the U.S. Department of State. Learn more about the ITAR here.

Use of AI in hiring

Hadrian uses AI-assisted tools in our recruiting and hiring processes to help our team work more efficiently. This may include tools that help organize and analyze recruiting data, as well as an AI-powered notetaker that can record and transcribe interviews and help coordinate feedback. These tools support our team and are not used to make hiring decisions. All candidate evaluations and hiring decisions are performed by humans. If an interview will be recorded, you will be notified in advance and may opt out at any time with no impact on your candidacy. Candidate data processed through these tools is subject to the same protections described in our Privacy Policy.

About Hadrian

Hadrianadri?ja?n?s]; 24 January 76 – 10 July 138) was Roman emperor from 117 to 138. He was born in Italica, a Roman municipium founded by Italic settlers in Hispania Baetica and he came from a branch of the gens Aelia that originated in the Picenean town of Hadria, the Aeli Hadriani. His father was of senatorial rank and was a first cousin of Emperor Trajan. Hadrian married Trajan's grand-niece Vibia Sabina early in his career before Trajan became emperor and possibly at the behest of Trajan's wife Pompeia Plotina. Plotina and Trajan's close friend and adviser Lucius Licinius Sura were well disposed towards Hadrian. When Trajan died, his widow claimed that he had nominated Hadrian as emperor immediately before his death. Rome's military and Senate approved Hadrian's succession, but four leading senators were unlawfully put to death soon after. They had opposed Hadrian or seemed to threaten his succession, and the Senate held him responsible for their deaths and never forgave him. He earned further disapproval among the elite by abandoning Trajan's expansionist policies and territorial gains in Mesopotamia, Assyria, Armenia, and parts of Dacia. Hadrian preferred to invest in the development of stable, defensible borders and the unification of the empire's disparate peoples. He is known for building Hadrian's Wall, which marked the northern limit of Britannia.
Learn more about Hadrian

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