Senior Data engineer

Devicemotion Technologies; Pune District; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Devicemotion Technologies in Pune is seeking a hands-on Data Engineer to design, build, and operate scalable data pipelines and data warehouses. You will work with Snowflake, Kafka, Python, and PySpark on cloud platforms like AWS/Azure/GCP to deliver robust data solutions.

The role requires 5–8 years of hands-on experience in data engineering, ETL/ELT, and distributed data processing, along with strong SQL and data modeling skills.

Qualifications

• Hands-on data engineering with scalable pipelines and data warehouses.
• Experience with Snowflake, Kafka, Python and PySpark.
• Cloud platforms such as AWS/Azure/GCP are a plus.
• Strong ETL/ELT, data modeling, and SQL understanding.

Responsibilities

• Design, develop, and maintain scalable data pipelines and ETL/ELT workflows.
• Build and optimize data solutions using Snowflake and cloud data warehouses.
• Develop data processing with Python and PySpark.
• Work with Kafka for real-time data ingestion and streaming.
• Develop and manage data engineering solutions on AWS or other clouds.
• Optimize pipelines for performance, reliability, scalability, and cost.
• Implement data quality, monitoring, and error handling.
• Collaborate with data scientists, analysts, engineers, and business teams.

Skills

Data Engineering

Snowflake

Python

PySpark

Apache Kafka

AWS/Azure/GCP

ETL/ELT

Data Modeling

Data Warehousing

SQL

Education

B.E./B.Tech in CS/IT

Tools

Kafka

PySpark

AWS

Azure

GCP

Airflow

dbt

Job description

Location: Pune (Baner)Experience: 5 to 8 yearsEmployment Type: Full-time

We are looking for a skilled Data Engineer with strong hands‑on experience in building and managing scalable data pipelines, data warehouses, and cloud-based data platforms.

The ideal candidate will have practical experience with Snowflake, Kafka, Python/PySpark, and AWS or another major cloud platform, along with a strong understanding of modern data engineering practices.

Key Responsibilities

• Design, develop, and maintain scalable data pipelines and ETL/ELT workflows.
• Build and optimize data solutions using Snowflake and cloud-based data warehouses.
• Develop data processing and transformation workflows using Python and PySpark.
• Work with Kafka for real-time data ingestion and streaming pipelines.
• Develop and manage data engineering solutions on AWS or other cloud platforms.
• Optimize data pipelines for performance, reliability, scalability, and cost.
• Implement data quality, monitoring, validation, and error‑handling mechanisms.
• Collaborate with data scientists, analysts, software engineers, and business teams to deliver reliable data solutions.

Required Skills

• Strong hands‑on experience in Data Engineering.
• Experience with Snowflake and modern data warehouse architectures.
• Strong programming experience in Python and/or PySpark.
• Hands‑on experience with Apache Kafka and data streaming.
• Experience with AWS, Azure, GCP, or another cloud platform.
• Strong understanding of ETL/ELT, data pipelines, data modeling, and data warehousing.
• Experience working with large-scale datasets and distributed data processing.
• Good understanding of SQL and database concepts.

Good to Have

• Experience with Apache Spark, Airflow, dbt, or similar data engineering tools.
• Experience with real-time/streaming data architectures.
• Knowledge of data lake and lakehouse architectures.
• Experience with data quality, governance, and observability.
• Familiarity with CI/CD and infrastructure-as-code practices.

What Were Looking For

We are looking for someone who is hands‑on, technically strong, and comfortable working on complex data engineering problems. Candidates with strong experience building production‑grade data pipelines and cloud‑based data platforms will be preferred.