Here are the details of the
role I need help with. Please have a look and let me know if you can help! It’s
W2 to TEKsystems, so I would need to get you a referral fee.
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Skills Required:
1. Databricks
2. Azure Data Factory
3. Python/PySpark
4. SQL
5. Manufacturing OR Industrial
Overview
TEKsystems is partnering with
AdvanSix to identify a skilled Data Engineer to support the buildout and
operation of the company's Unified Data Platform. This role will focus on
integrating manufacturing and enterprise data across Operational Technology
(OT) and Information Technology (IT) environments to enable advanced analytics,
reporting, and AI-driven insights.
A major focus of this
position will be establishing and supporting real-time data ingestion from
manufacturing equipment and operational systems into Azure-based data
platforms. The engineer will work closely with plant teams to safely connect
historian, process, and equipment data using technologies such as Azure IoT,
OPC UA, MQTT, and industrial data brokers, enabling advanced analytics and
yield prediction capabilities across manufacturing operations.
The ideal candidate will have
strong experience building enterprise-scale data pipelines in Azure and will be
comfortable working directly with manufacturing systems, historians, and
real-time industrial data streams. This role will contribute to governed,
scalable, and reliable data products that improve operational efficiency,
process visibility, and predictive manufacturing outcomes.
Key Responsibilities
Data Engineering & Platform
Development
Design, build, and maintain
scalable data pipelines supporting batch, CDC, API, and real-time streaming
workloads.
Ingest data from enterprise
and manufacturing systems including SAP S/4HANA, SAP DataSphere, historians,
LIMS, transportation systems, HSE applications, and other operational
platforms.
Develop and support landing,
curated, and semantic data layers that serve analytics, reporting, AI, and
machine learning initiatives.
Build and optimize
Azure-based solutions using Databricks, Synapse/Fabric, Azure Data Factory,
ADLS/OneLake, Azure SQL, and Azure Key Vault.
Implement data contracts,
schema versioning, partitioning strategies, and slowly changing dimension
methodologies.
Tune data pipelines and
storage architectures to improve performance, scalability, reliability, and
cost efficiency.
Manufacturing Data & OT
Integration
Establish secure ingestion of
manufacturing and industrial data into Azure analytics platforms.
Configure and support
real-time streaming architectures using Azure IoT technologies, OPC UA, MQTT,
historians, and event-driven operational data sources.
Partner with plant controls
and operations teams to safely connect OT systems to enterprise analytics
environments using brokered architectures and DMZ patterns.
Support predictive analytics
initiatives focused on manufacturing yield optimization, process performance
monitoring, and operational insights.
Help ensure OT integrations
follow plant safety, cybersecurity, and change management standards.
Data Quality, Governance &
Observability
Implement automated data
validation, monitoring, and testing frameworks.
Develop controls for
freshness, completeness, accuracy, schema validation, and data drift detection.
Establish lineage tracking,
alerting, and operational dashboards to improve platform reliability.
Create runbooks and
operational procedures supporting incident response and troubleshooting.
Support compliance with data
governance, retention, security, and master data management standards.
DevOps & Reliability
Engineering
Build and maintain Git-based
CI/CD pipelines supporting automated testing and deployment.
Support environment
management, release processes, and deployment automation.
Optimize cloud platform
consumption through cluster sizing, autoscaling, caching strategies, and
resource tuning.
Contribute to platform
reliability, performance improvements, and FinOps initiatives.
Stakeholder Collaboration
Partner closely with
Reporting & BI teams to deliver trusted semantic models and Power BI
datasets.
Collaborate with SAP,
Governance, Cybersecurity, AI Engineering, and Manufacturing Operations
stakeholders.
Create technical
documentation, data dictionaries, architecture diagrams, and knowledge-transfer
materials.
Required Qualifications
5+ years of experience as a
Data Engineer building production-scale data solutions.
Strong experience designing
batch, CDC, API, and streaming data pipelines.
Hands-on expertise with Azure
Databricks, Azure Data Factory, Azure Synapse Analytics and/or Microsoft
Fabric, Azure Data Lake Storage, Azure SQL / SQL Managed Instance, and Azure
Key Vault.
Strong SQL and Python/PySpark
development experience.
Experience with Spark
Structured Streaming and performance optimization.
Proven experience building
integrations using REST and SOAP APIs.
Hands-on experience working
with JSON, XML, Postman, OAuth2, Bearer Tokens, and API security protocols.
Experience developing
resilient ingestion frameworks that handle pagination, throttling, retries, and
error recovery.
Experience implementing
automated testing, monitoring, observability, and CI/CD practices.
Familiarity with SAP S/4HANA
and SAP DataSphere.
Experience supporting OT
environments and industrial data integration technologies such as process
historians, OPC UA, MQTT, event and batch data frameworks, and ISA-95 / ISA-99
concepts.
Understanding of Power BI
semantic models, row-level security, and downstream AI/ML data consumption
patterns.
Preferred Qualifications
Experience within
manufacturing, chemical, industrial, or process-driven organizations.
Experience implementing Azure
IoT-based data streaming solutions.
Strong understanding of
time-series data architectures and industrial analytics.
Experience with data quality
frameworks such as Great Expectations or equivalent patterns.
Familiarity with master data
management, data lineage, cataloging, and governance solutions.
Experience working with LIMS,
TMS, WMS, HSE, and manufacturing historian systems.
Exposure to Lean
Manufacturing, Six Sigma, or continuous improvement methodologies.
Understanding of cloud cost
optimization and FinOps principles.
Additional Information
Hybrid role requiring 3-4
days onsite per week at one of the Virginia manufacturing facilities listed
above.
Candidates must be
comfortable working directly with manufacturing operations and plant
stakeholders.
W2 only; third-party
candidates.
No current or future visa
sponsorship available.
Experience integrating
real-time manufacturing equipment and operational data into Azure analytics
platforms is highly preferred.
Why This Opportunity?
This role offers the
opportunity to help modernize data capabilities across a major manufacturing
organization by connecting industrial operations with enterprise analytics. The
Data Engineer will directly contribute to initiatives that enable real-time
visibility, predictive yield analysis, AI readiness, and data-driven decision
making across AdvanSix's manufacturing footprint.
Information
Locations Position Open to Only localsIndustry Information TechnologyStatus OpenJob Age 9 Day'sCreated Date 07/28/2026No.of Positions 1Duration long termZip Code
