About The Company

GyanSys Inc. is a leading global systems integrator and technology consulting firm dedicated to helping enterprises accelerate their digital transformation journeys. With a focus on cutting-edge solutions, GyanSys specializes in delivering comprehensive services across SAP, Cloud, Data & Analytics, Artificial Intelligence, and Intelligent Automation. The company partners with top technology providers to develop scalable, business-driven solutions tailored to diverse industry needs worldwide.

GyanSys prides itself on its commitment to excellence, customer-centric approach, and fostering a culture of continuous innovation and professional development.

About The Role

We are seeking a highly skilled and experienced Senior Data Engineer / Consultant to join our expanding Data & Analytics practice. The ideal candidate will possess a strong background in designing, developing, and optimizing enterprise-scale data engineering solutions across modern cloud platforms. This role offers an exciting opportunity to work on cutting-edge technologies such as Microsoft Fabric, Azure Data Engineering, Databricks, PySpark, and Apache Spark, contributing to large-scale data initiatives for global clients.

The Senior Data

Engineer / Consultant will collaborate closely with architects, business stakeholders, data scientists, and cross-functional teams to build robust, scalable data pipelines and analytics solutions that enable data-driven decision-making and business growth.

Qualifications The candidate should hold a Bachelor's or Master’s degree in Computer Science, Information Technology, Engineering, or a related field. A minimum of four years of professional experience in data engineering or related roles is required.

Relevant certifications such as Microsoft Certified: Fabric Data Engineer Associate, Azure Data Engineer Associate, or Databricks Certified Data Engineer are highly preferred.

Experience working with enterprise data platforms, cloud environments, and modern data architecture principles will be advantageous.



The ideal candidate should demonstrate a strong understanding of data modeling, data warehousing, and data lake concepts, along with proficiency in relevant tools and programming languages.

Responsibilities

- Design, develop, and maintain scalable ETL/ELT data pipelines to support enterprise data platforms and analytics initiatives.
- Implement data engineering solutions utilizing Microsoft Fabric, Azure Data Factory, Databricks, PySpark, Spark SQL, and Python to process structured, semi-structured, and unstructured data.
- Build and optimize data pipelines for various data types, ensuring high performance, reliability, and cost efficiency.
- Work extensively with Microsoft Fabric components such as Fabric Data Factory, Lakehouse, Warehouse, Dataflows, and Notebooks to develop integrated data solutions.
- Develop and optimize Databricks notebooks, Spark jobs, Delta Lake pipelines, and Databricks workflows to facilitate data processing and analytics.
- Implement Medallion Architecture and modern Lakehouse/Data Platform architectures to ensure scalable and maintainable data solutions.
- Integrate data from multiple sources including SQL Server, Oracle, PostgreSQL, APIs, cloud storage, ERP systems, and SaaS applications to create unified data views.
- Design efficient data models, data warehouses, data lakes, and Lakehouse solutions aligned with business requirements and best practices.
- Optimize data pipelines, Spark jobs, SQL queries, clusters, and storage to maximize performance and minimize costs.
- Implement data quality, validation, monitoring, governance, security, and compliance practices to ensure data integrity and regulatory adherence.




- Develop and maintain CI/CD pipelines using Azure DevOps, GitHub, and other version control tools to streamline deployment and updates.
- Troubleshoot production issues, conduct root-cause analysis, and implement performance improvements to ensure system stability and efficiency.
- Collaborate effectively with solution architects, business analysts, data scientists, and BI teams to deliver end-to-end data solutions.
- Participate in technical design discussions, code reviews, documentation, and knowledge-sharing initiatives to promote best practices.
- Mentor junior engineers and contribute to the development of technical standards and best practices within the team.

Benefits GyanSys offers a competitive benefits package designed to support the well-being and professional growth of its employees. Employees are eligible for comprehensive health insurance, including medical, dental, and vision coverage. The company provides opportunities for continuous learning through training programs, certifications, and participation in industry conferences. GyanSys fosters a collaborative and inclusive work environment that encourages innovation and career advancement. Additionally, employees enjoy flexible work arrangements, performance-based incentives, and recognition programs that celebrate achievements and contributions. The company also emphasizes work-life balance, ensuring a supportive environment where employees can thrive both professionally and personally.

Equal Opportunity

GyanSys Inc. is committed to creating an inclusive and diverse workplace. We provide equal employment opportunities to all qualified individuals regardless of race, color, religion, gender, sexual orientation, gender identity or expression, age, national origin, disability, or any other characteristic protected by applicable laws. We believe that diverse teams foster innovation and creativity, and we are dedicated to building a workplace where everyone feels valued, respected, and empowered to contribute to our collective success.

📌 Data Engineer (India)
🏢 FetchJobs.co
📍 India