to collect, clean, transform, and integrate data from multiple manufacturing sources (e.g., SCADA, ERP, MES systems).
Build and maintain
data warehouses/data lakes
to support real-time and batch analytics.
Develop
data models and schemas
that align with manufacturing processes and KPIs.
Collaborate with plant operations, engineering, and IT teams to understand data requirements and optimize data flows.
Ensure data quality, consistency, and governance standards are maintained.
Support advanced analytics, dashboarding, and AI/ML use cases by making reliable plant data available.
Monitor data systems to ensure performance and resolve issues promptly.
Required Skills & Experience:
Strong
ETL and data engineering
experience (e.g., using Python, SQL).
Proven experience with
data warehouses or data lakes
in industrial/manufacturing environments.
Strong SQL and NoSQL
experience (e.g., MongoDB).
Experience with
cloud data platforms
(e.g., Google Cloud Platform, Snowflake, Azure, or AWS).
Data modeling skills and understanding of relational as well as time-series/IoT data.
Preferred Skills:
Experience with
Graph Databases
(e.g., Neo4j).
Certifications in cloud platforms (e.g., GCP Data Engineer) are a plus.
Experience in
automotive or discrete manufacturing
data projects is strongly preferred.
Familiarity with tools like
Tableau, Power BI
, or similar for data visualization.
Domain Knowledge:
Prior experience in
automotive or manufacturing plants
is strongly preferred.
Understanding of
plant floor systems
(e.g., PLCs, sensors, SCADA) and data collection methods.
Ability to work with operations teams and translate manufacturing needs into data solutions.
Soft Skills:
Excellent problem-solving and analytical skills.
Strong communication and stakeholder management.
Ability to work in a fast-paced, cross-functional environment.
Job Type: Contractual / Temporary
Contract length: 6 months
Pay: ?400,000.00 - ?600,000.00 per year
Benefits:
Health insurance
Provident Fund
Work Location: In person
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