Data Engineer in Pune, Mahārāshtra at Ascentt

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.

Data Engineer – Enterprise Data Platforms & AI-Driven Engineering

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

We are looking for engineers who are:

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.