We are looking for a Senior Data Engineer with robust expertise in Azure Databricks, PySpark, and distributed computing to develop and optimize scalable ETL pipelines for manufacturing analytics. The role involves working with high-frequency industrial data to enable real-time and batch data processing.

Responsibilities
Build scalable real-time and batch processing workflows using Azure Databricks, PySpark, and Apache Spark.
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 the automation team, data scientists, and engineers to provide clean, structured data for AI/ML models.

Requirements
Bachelor's or Master's degree in Computer Science, Information Technology, or a related field.
7+ years of experience in core data engineering, with a robust focus on cloud platforms such as Azure (preferred), AWS, or GCP.
Proficiency in PySpark, Azure Databricks, Python, Apache Spark, etc.
2 years of team handling experience.
Expertise in relational databases (e. g., SQL Server, PostgreSQL), time series databases (e. g., InfluxDB), and NoSQL databases (e. g., MongoDB, Cassandra).
Experience in containerization (Docker, Kubernetes).
Robust analytical and problem-solving skills with attention to detail.
Good to have MLOps and 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

This job was posted by Dr Soumya Sahadevan from Tvarit.

📌 Senior Data Engineer Pune (India)
🏢 Tvarit
📍 India