Posted:1 day ago|
Platform:
On-site
Full Time
· Perform data pre-processing, including cleaning, transformation, deduplication, normalization, encoding, and scaling to ensure high-quality input for downstream analytics.
· Design and maintain cloud-based data architectures, including data lakes, lakehouses, and warehouses, following Medallion Architecture.
· Deploy and optimize data solutions on Azure (preferred), AWS, or GCP with a focus on performance, security, and scalability.
· Develop and optimize ETL/ELT pipelines for structured and unstructured data from IoT, MES, SCADA, LIMS, and ERP systems. · Automate data workflows using CI/CD and DevOps best practices, ensuring security and compliance with industry standards
· Monitor, troubleshoot, and enhance data pipelines for high availability and reliability.
· Utilize Docker and Kubernetes for scalable data processing.
· Collaborate with automation team, data scientists and engineers to provide clean, structured data for AI/ML models.
· 7+ years of experience in core data engineering, with a strong focus on cloud platforms such as Azure (preferred), AWS, or GCP · Proficiency in PySpark, Azure Databricks, Python and Apache Spark, etc.
. 2 years of team handling experience.
· Expertise in relational databases (e.g., SQL Server, PostgreSQL), time series databases (e.g. Influx DB), and NoSQL databases (e.g., MongoDB, Cassandra) · Experience in containerization (Docker, Kubernetes).
· Strong analytical and problem-solving skills with attention to detail.
· Good to have MLOps, DevOps including model lifecycle management
· Excellent communication and collaboration skills, with a proven ability to work effectively as a team player.
· Comfortable working in a dynamic, fast-paced startup environment, adapting quickly to changing priorities and responsibilities.
Interested candidate can send resume at shubhamn@usil.tech
USIL Technologies
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