Data Engineer

Ascentt; Pune District; On-site; INR 1,200,000 - 2,500,000; Full time

Job summary

Ascentt is building cutting-edge data analytics and AI/ML solutions for global automotive and manufacturing leaders. We are seeking a Data Engineer to design scalable data pipelines and modern analytics architectures, collaborating with business and technical stakeholders across the organization.

The ideal candidate has 5+ years in data engineering, hands-on experience with Databricks, Snowflake, Airflow, and cloud platforms (AWS/Azure/GCP).

Qualifications

• 5+ years of experience in Data Engineering or related enterprise data platform roles.
• Strong hands-on experience in building enterprise-scale data pipelines and distributed data processing systems.
• Deep expertise in Python programming for data engineering applications.
• Experience with Databricks and Snowflake; data orchestration tools (Airflow, Dagster, Prefect).
• Cloud platforms such as AWS, Azure, or GCP; large datasets in enterprise environments.
• Knowledge of data lake, lakehouse, and modern data warehouse architectures.
• Experience with Spark / PySpark and distributed computing; data governance and metadata management.

Responsibilities

• Design, develop, optimize, and maintain scalable data pipelines for large-scale enterprise data processing.
• Build ETL/ELT workflows using orchestration frameworks and cloud-native technologies.
• Develop and manage data architectures using platforms such as Databricks and Snowflake.
• Work with structured, semi-structured, and unstructured data across enterprise systems.
• Architect high-performance data engineering solutions with scalable design.
• Collaborate with stakeholders to translate data requirements into technical solutions.
• Lead technical discussions and provide guidance to junior engineers.
• Implement data quality, governance, monitoring, security, and observability best practices.
• Optimize data processing performance, storage, and cost in cloud environments.
• Leverage AI-assisted development tools to improve productivity and code quality.
• Contribute to platform modernization and architecture reviews.

Skills

Python

Databricks

Snowflake

Airflow

AWS/Azure/GCP

Spark/PySpark

Data modeling

CI/CD for data

GitHub Copilot

Mentoring

Tools

Docker

Kubernetes

GitHub Copilot

Job description

Ascentt is building cutting-edge data analytics & AI/ML solutions for global automotive and manufacturing leaders. We turn enterprise data into real-time decisions using advanced machine learning and GenAI. Our team solves hard engineering problems at scale, with real-world industry impact. We’re hiring passionate builders to shape the future of industrial intelligence.

We are looking for a highly skilled and passionate Data Engineer to join our high-performance engineering team. The ideal candidate should have strong experience in designing and building scalable enterprise-grade data platforms, modern data pipelines, and cloud-based analytics architectures. This role requires both strong technical expertise and the ability to collaborate with business and technical stakeholders across the organization.

Key Responsibilities

• Design, develop, optimize, and maintain scalable data pipelines for large-scale enterprise data processing.
• Build robust ETL/ELT workflows using modern orchestration frameworks and cloud-native technologies.
• Develop and manage enterprise data architectures using platforms such as Databricks and Snowflake.
• Work with structured, semi-structured, and unstructured data across multiple enterprise systems.
• Architect high-performance data engineering solutions capable of processing large volumes of data efficiently.
• Collaborate with architects, business stakeholders, analytics teams, and product teams to understand data requirements and translate them into scalable technical solutions.
• Lead technical discussions and provide guidance to junior and mid-level engineers.
• Implement data quality, governance, monitoring, security, and observability best practices.
• Optimize data processing performance, storage strategies, and cost efficiency in cloud environments.
• Use AI-assisted development tools such as GitHub Copilot effectively to improve engineering productivity and code quality.
• Contribute to enterprise-level solution design, platform modernization, and innovation initiatives.
• Participate in architecture reviews, code reviews, and technical mentoring.

Required Skills & Experience

• 5+ years of experience in Data Engineering or related enterprise data platform roles.
• Strong hands-on experience in building enterprise-scale data pipelines and distributed data processing systems.
• Deep expertise in Python programming for data engineering applications.
• Strong experience with:
• Databricks
• Snowflake
• Data orchestration tools (Airflow, Dagster, Prefect, or equivalent)
• Cloud platforms such as AWS, Azure, or GCP
• Experience handling very large datasets in enterprise environments.
• Strong understanding of data lake, lakehouse, and modern data warehouse architectures.
• Experience with Spark / PySpark and distributed computing frameworks.
• Good understanding of data modeling, data governance, metadata management, and performance tuning.
• Experience working with APIs, streaming pipelines, and batch processing frameworks.
• Strong understanding of CI/CD practices, DevOps, and infrastructure automation for data platforms.
• Familiarity with AI-assisted development tools including GitHub Copilot.

Soft Skills

• Excellent communication and stakeholder management skills.
• Ability to work closely with cross-functional business and technical teams.
• Strong problem-solving and analytical thinking capabilities.
• Ability to mentor, guide, and support engineering teams.
• Self-driven, proactive, and capable of operating in fast-paced enterprise environments.
• Strong ownership mindset and commitment to engineering excellence.

Preferred Qualifications

• Experience in enterprise-scale analytics or AI/ML data platforms.
• Exposure to real-time data processing and event-driven architectures.
• Experience with containerization and orchestration technologies such as Docker and Kubernetes.
• Understanding of enterprise security and compliance requirements.
• Prior experience working in high-performance engineering or consulting teams is a plus.

What We Are Looking For

• Passionate about solving complex data engineering challenges.
• Comfortable working with large-scale enterprise data ecosystems.
• Capable of designing architecture, not just writing code.
• Eager to innovate and adopt modern AI-assisted engineering practices.
• Strong team players with leadership potential and excellent communication abilities.