Senior Data Engineer

TVARIT; Pune District; On-site; INR 4,500,000 - 7,500,000; Full time

Job summary

TVARIT GmbH in Pune, India, is seeking a Senior Data Engineer to build scalable real-time and batch ETL pipelines for manufacturing analytics, leveraging Azure Databricks, PySpark, and distributed computing.

You will design cloud data architectures (data lakes, lakehouses, warehouses) and deploy solutions on Azure/AWS/GCP, while ensuring security, scalability, and collaboration with data scientists and automation teams.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, IT, or related field.
• 5+ years in core data engineering with cloud platforms (Azure preferred).
• Proficiency in PySpark, Azure Databricks, Python and Apache Spark.
• Experience with Docker and Kubernetes for containerized data processing.
• Strong communication and collaborative skills.

Responsibilities

• Build real-time and batch ETL/ELT pipelines for manufacturing analytics.
• Design cloud data architectures (data lakes, lakehouses, warehouses) per Medallion Architecture.
• Deploy and optimize data solutions on Azure/AWS/GCP with security in mind.
• Collaborate with data scientists and automation team to prepare clean data.
• Monitor and improve data pipelines for reliability and scalability.

Skills

PySpark

Azure Databricks

Python

Apache Spark

ETL pipelines

Distributed computing

Docker

Kubernetes

Team leadership

Education

Bachelor’s or Master’s degree in Computer Science/IT or related field

Tools

SQL Server

PostgreSQL

InfluxDB

MongoDB

Cassandra

Job description

TVARIT GmbH specializes in developing and delivering cutting-edge artificial intelligence (AI) solutions for the metal industry, including steel, aluminum, copper, cast iron, and more. Our software products empower customers to make intelligent, data-driven decisions, driving advancements in Predictive Quality (PsQ), Predictive Maintenance (PdM), and Energy Consumption Reduction (PsE), etc. With a strong portfolio of renowned reference customers, state-of-the-art technology, a talented research team from prestigious universities, and recognition through esteemed awards such as the EU Horizon 2020 AI Prize, TVARIT is recognized as one of the most innovative AI companies in Germany and Europe. We are seeking a self-motivated individual with a positive "can-do" attitude and excellent oral and written communication skills in English to join our team.

Job Description

We are looking for a Senior Data Engineer with strong 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.

Key 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 automation team, data scientists and engineers to provide clean, structured data for AI/ML models.

Qualifications

Bachelor’s or Master’s degree in Computer Science, Information Technology, or a related field. Candidates from premier engineering institutes such as IITs, IIITs, NITs, or BITS are preferred.

Desired Skills

• 5+ 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.