Sr. Data Engineer | ErayTec | Remote (USA)

Tech Junction Ltd; Northern (KY); Remote; USD 140,000 - 180,000; Full time

Job summary

ErayTec seeks an experienced Sr. Data Engineer to own end-to-end data pipelines for OEE, Connected Worker, and Golden Batch analytics. You will lead design and delivery of production-grade data workflows using Spark, Python, and SQL on Azure Data Factory and Azure Databricks.

Remote role supporting US operations with strong collaboration across engineering and business teams. You will optimize data architecture, ingest high-frequency telemetry, and ensure data quality and performance in a

Qualifications

• 7+ years of total IT experience with 5+ years in data engineering.
• Proven proficiency in Spark, Python and SQL for production-grade pipelines.
• Experience designing pipelines for manufacturing metrics (OEE, Connected Worker, Golden Batch).

Responsibilities

• Design, develop, test and deploy production-grade data pipelines and architectures.
• Build pipelines for OEE metrics, Connected Worker events and Golden Batch data.
• Implement and optimize cloud-native workflows using Azure Data Factory and Azure Databricks.
• Model and ingest time-series manufacturing data and telemetry patterns.
• Ensure scalability, fault tolerance and data quality across clusters.
• Collaborate with cross-functional teams in a remote environment.
• Maintain technical docs and data governance standards.
• Perform code reviews and performance tuning for large data jobs.

Skills

Apache Spark

Python

SQL

Azure Data Factory

Azure Databricks

Education

Bachelor’s or Master’s degree in CS/SE/IT

Tools

Azure Data Factory

Azure Databricks

Job description

Position Summary:

ErayTec is actively seeking an experienced, high-caliber, and technical Sr. Data Engineer with 7+ years of professional data engineering experience to join our offshore-supported remote operations team on a 12-month contract basis. In this critical data engineering role, you will be responsible for designing and building production-grade data pipelines for OEE metrics, Connected Worker events, and Golden Batch analytical data. You will leverage your strong expertise in Apache Spark, Python, SQL, and cloud-native data platforms like Azure Data Factory and Azure Databricks to drive advanced manufacturing analytics. This opportunity offers competitive compensation, executive technical visibility, and excellent professional growth prospects within a leading global technology and consulting enterprise (Note: Strictly open to candidates based in the USA only).

Detailed Job Description:

As a Sr. Data Engineer supporting advanced manufacturing analytics via ErayTec, you will take full operational, tactical, and technical ownership of end-to-end data pipeline development and cloud data architecture. Your day-to-day responsibilities include designing and building production-grade data pipelines for Overall Equipment Effectiveness (OEE) metrics, Connected Worker events, and Golden Batch analytical data. You will leverage strong hands-on experience with Apache Spark, Python, and SQL, while working extensively with cloud data platforms such as Azure Data Factory, Azure Databricks, or equivalent cloud-native services. Furthermore, you will interpret manufacturing data models, time-series data streams, and equipment telemetry patterns to ensure high-performance analytics, collaborating closely with cross-functional technical and business stakeholders.

Key Responsibilities:

• Design, develop, test, and deploy production-grade data pipelines and data processing architectures using Apache Spark, Python, and SQL.
• Build specialized data pipelines for OEE (Overall Equipment Effectiveness) metrics, Connected Worker events, and Golden Batch analytical datasets.
• Implement and optimize cloud-native data workflows using Azure Data Factory, Azure Databricks, and equivalent cloud services.
• Model and ingest manufacturing data, high-frequency time-series data streams, and complex equipment telemetry patterns.
• Ensure data pipeline scalability, fault tolerance, data quality, and high performance across distributed compute clusters.
• Collaborate effectively with technical engineering squads, data architects, and business stakeholders in a remote environment.
• Maintain comprehensive technical documentation, pipeline architecture diagrams, and data governance standards.
• Perform thorough code reviews, performance tuning, and troubleshooting for large-scale data transformation jobs.

Required Qualifications & Skills:

• Bachelor’s or Master’s degree in Computer Science, Software Engineering, Data Engineering, Information Technology, or a related technical discipline.
• Minimum of 7+ years of total professional IT experience with at least 5+ years of hands-on data engineering experience.
• Strong, proven proficiency in Apache Spark, Python, and advanced SQL querying.
• Extensive experience designing and building production-grade data pipelines for manufacturing metrics (OEE, Connected Worker, Golden Batch).
• Deep expertise in cloud data platforms such as Azure Data Factory, Azure Databricks, or equivalent cloud-native data services.
• Good conceptual understanding of manufacturing data models, time-series telemetry, and industrial IoT data patterns.
• Mandatory active LinkedIn profile and exceptional verbal and written communication skills for remote client collaboration.
• Strict legal eligibility to work and reside in the USA (Offshore opportunity requiring candidates based in the USA only).

Nice-to-Have Skills:

• Prior professional experience in smart manufacturing, Industry 4.0, or industrial automation analytics.
• Certifications in Azure Data Engineering (e.g., Microsoft Certified: Azure Data Engineer Associate) or Databricks.
• Experience with streaming data ingestion using Apache Kafka or Azure Event Hubs.
• Familiarity with Delta Lake architecture and Medallion data lakehouse patterns.

Contract and Salary:

Salary/Rate: Market Competitive / 12-Month Contract Package

Deadline: Open until filled (Urgent Requirement)

Notice Period: Immediate to 2 Weeks

Contract Duration: 12 Months Contract / Remote (USA Candidates Only)