Data Engineer

Altumind Digital Consulting LLP; Bengaluru; On-site; INR 1,200,000 - 2,000,000; Full time

Job summary

Altumind Digital Consulting LLP in Bengaluru, India seeks an experienced data engineer to collaborate with ML teams to deploy and monitor models in production, design experiments, and ensure high data quality and governance in complex architectures.

You will build and scale data pipelines, optimize performance, and work with SQL/NoSQL, Python, Spark, and cloud platforms (AWS/GCP/Azure). Experience with ML pipelines and NLP technologies is valued.

Qualifications

• 5-6 years of data engineering experience, with a proven track record in building scalable data systems.
• Proficiency in SQL & No SQL databases, Python, and distributed processing technologies such as Apache Spark.
• Strong understanding of data warehousing concepts, data modelling, and architecture principles.
• Expertise in cloud platforms (AWS, GCP, Azure) and managing cloud-based data systems would be an added advantage.
• Hands‑on experience building and maintaining machine learning pipelines and utilizing tools like MLflow, Kubeflow, or similar frameworks.
• Experience with search, recommendation engines, or NLP (Natural Language Processing) technologies.
• Solid foundation in statistics and experimental design, particularly in relation to machine learning systems.
• Strong problem‑solving skills and ability to work independently and in a team‑oriented environment.

Responsibilities

• Collaborate closely with Machine Learning (ML) teams to deploy and monitor models in production, ensuring optimal performance and reliability.
• Design and implement experiments, and apply statistical analysis to validate model solutions and results.
• Lead efforts in ensuring high-quality data, proper governance practices, and excellent system performance in complex data architectures.
• Develop, maintain, and scale data pipelines, enabling machine learning and analytical models to function efficiently.
• Monitor and troubleshoot issues within data systems, resolving performance bottlenecks and implementing best practices.

Skills

SQL & NoSQL

Python

Apache Spark

Data warehousing

Cloud platforms (AWS, GCP, Azure)

ML pipelines

MLflow / Kubeflow

NLP / Search / Recommendation

Statistics & experimental design

Analytical / problem solving

Job description

Responsibilities

Collaborate closely with Machine Learning (ML) teams to deploy and monitor models in production, ensuring optimal performance and reliability.

Design and implement experiments, and apply statistical analysis to validate model solutions and results.

Lead efforts in ensuring high-quality data, proper governance practices, and excellent system performance in complex data architectures.

Develop, maintain, and scale data pipelines, enabling machine learning and analytical models to function efficiently.

Monitor and troubleshoot issues within data systems, resolving performance bottlenecks and implementing best practices.

Required Skills and Experience

• 5-6 years of data engineering experience, with a proven track record in building scalable data systems.
• Proficiency in SQL & No SQL databases, Python, and distributed processing technologies such as Apache Spark.
• Strong understanding of data warehousing concepts, data modelling, and architecture principles.
• Expertise in cloud platforms (AWS, GCP, Azure) and managing cloud-based data systems would be an added advantage.
• Hands‑on experience building and maintaining machine learning pipelines and utilizing tools like MLflow, Kubeflow, or similar frameworks.
• Experience with search, recommendation engines, or NLP (Natural Language Processing) technologies.
• Solid foundation in statistics and experimental design, particularly in relation to machine learning systems.
• Strong problem‑solving skills and ability to work independently and in a team‑oriented environment.