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Senior Data Engineer (Hybrid) – Cloud Data Pipelines & Manufacturing IoT

abn innovations United State
Relocation
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AI Summary

Design and build scalable cloud data pipelines for high-volume manufacturing and IoT data using Spark, Kafka, and Delta Lake. Leverage SQL and Python to architect medallion/lakehouse architectures on Databricks, Snowflake, or cloud platforms. Drive operational efficiency with real-time OT/IT integration and industrial analytics.

Key Highlights
5+ years of experience in data engineering with hands-on cloud architecture (Databricks, Snowflake, AWS, Azure)
Hybrid role (4 days onsite, 1 day WFH) with relocation assistance provided by company
No third-party C2C candidates; direct hire only
Key Responsibilities
Design and implement scalable cloud data pipelines for high-volume manufacturing and IoT data using Spark, Kafka, and Delta Lake
Develop and maintain medallion/lakehouse architectures on Databricks, Snowflake, AWS, or Azure platforms
Bridge OT/IT systems using industrial protocols (OPC-UA, MQTT, Modbus) for real-time data extraction and integration
Technical Skills Required
Python SQL Apache Spark
Benefits & Perks
Relocation assistance provided by company
Hybrid work arrangement (4 days onsite, 1 day remote)
No third-party C2C restrictions
Nice to Have
8–10 years of experience in manufacturing with hands-on shop floor operations, production planning, and systems (MES, SCADA, ERP)
Proficient in industrial protocols (OPC-UA, MQTT, Modbus)
Applied experience with OEE, Six Sigma, SPC, and lean methodologies

Job Description


No third-party C2C candidates. This is a direct hire full-time role.


Client is unable to sponsor visa at this time.


Relocation assistance will be provided by company.


This is a hybrid role with 4 days onsite/ 1 day WFH


Must have skills: 

  • Minimum 5+ years of experience (No limit for a right candidate)
  • Strong in SQL and Python proficiency with hands-on experience in medallion/Lakehouse architectures on Databricks, Snowflake, AWS, or Azure.

 

Job Overview:

  • Data Engineering Skilled in building scalable cloud data pipelines for high-volume manufacturing and IoT data using Spark, Kafka, Airflow, and Delta Lake.
  • Strong SQL and Python proficiency with hands-on experience in medallion/ Lakehouse architectures on Databricks, Snowflake, AWS, or Azure.

 

Good to Have:

  • Manufacturing 8–10 years in manufacturing (optional) with hands-on experience in shop floor operations, production planning, and systems including MES, SCADA, and ERP.
  • Proficient in industrial protocols (OPC-UA, MQTT, Modbus) with ability to bridge OT/IT systems for real-time data extraction.
  • Applied experience with OEE, Six Sigma, SPC, and lean methodologies to drive measurable gains in yield, uptime, and efficiency.



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