Data Engineer
First seen by Alion on Aug 4, 2026.
Company Overview :
Gigaforce is a technology-driven organization focused on building scalable AI-powered platforms that streamline complex operational workflows. Operating at the intersection of data science and enterprise software, the company develops high-performance solutions that enable businesses to leverage machine learning for real-time decision-making. With a culture rooted in engineering excellence and rapid innovation, Gigaforce provides a collaborative environment for professionals to solve large-scale data challenges in the evolving AI landscape.
Role Overview :
As a Data Engineer for the AI Data Platform, you will be responsible for architecting and maintaining the robust data pipelines that fuel our machine learning models. You will work closely with data scientists, software engineers, and product managers to transform raw, high-volume data into actionable insights.
Your day-to-day will involve building scalable infrastructure, ensuring data integrity, and optimizing processing frameworks to support our growing AI ecosystem. By bridging the gap between raw data ingestion and model deployment, you will directly influence the performance and reliability of our AI-driven product offerings.
Key Responsibilities :
- Design and implement scalable ETL/ELT pipelines to ingest, process, and store large-scale datasets from diverse sources.
- Develop and maintain high-performance data workflows using Apache Airflow to ensure timely and accurate data availability for downstream AI models.
- Architect efficient data models that support complex analytical queries and machine learning feature engineering requirements.
- Implement real-time data streaming solutions using Kafka to facilitate low-latency data processing and model inference.
- Establish and enforce rigorous data quality frameworks to monitor, validate, and remediate data inconsistencies across the platform.
- Optimize Spark-based processing jobs to improve computational efficiency and reduce latency in large-scale data transformations.
- Collaborate with cross-functional teams to integrate data engineering best practices into the end-to-end machine learning lifecycle.
Required Skillset :
- Demonstrated proficiency in writing complex SQL queries and optimizing database performance for large-scale analytical workloads.
- Strong programming capabilities in Python, with experience in building production-grade data processing applications.
- Proven ability to design and manage distributed data processing systems using Spark and Kafka in cloud-based environments.
- Expertise in data modeling techniques that support both structured and semi-structured data for AI applications.
- Excellent communication skills with the ability to translate technical data challenges into clear solutions for non-technical stakeholders.
- Strong analytical mindset with a focus on maintaining high standards of data quality and system reliability.
- Ability to thrive in a fast-paced, hybrid work environment based in Noida, collaborating effectively with distributed teams.
- Candidates should possess 3 - 5 years of relevant experience in data engineering or a closely related technical field.
Skills
Artificial Intelligence, Data Engineering, ETL, Data Integrity, Data Science, Apache Airflow, Data Modeling, Data Quality, SQL, Python, Spark