Company Overview :

Sysmind is a global technology services and consulting firm that specializes in delivering high-impact digital transformation solutions. We partner with enterprises across the healthcare, finance, and retail sectors to modernize their data infrastructure and accelerate decision-making through advanced analytics. With a focus on engineering excellence and scalable architecture, we empower our clients to navigate complex data landscapes and maintain a competitive edge in an increasingly data-driven market.

Role Overview :

As a Senior Big Data Engineer, you will be at the forefront of designing and maintaining robust data pipelines that process massive datasets. You will work closely with cross-functional engineering teams and data architects to translate complex business requirements into scalable technical solutions. Your primary impact will be ensuring the reliability, performance, and efficiency of our data processing frameworks, directly influencing the quality of insights delivered to our global client base.

Key Responsibilities :

- Architect and optimize high-performance data processing pipelines using Apache Spark and Scala to ensure timely data availability for downstream analytics.

- Manage and tune Big Data clusters within Hadoop environments, focusing on resource optimization via YARN to maximize throughput and minimize latency.

- Execute complex data modeling tasks to structure raw data into meaningful formats that support business intelligence and reporting needs.

- Collaborate with infrastructure teams to maintain HDFS storage systems, ensuring data integrity, security, and high availability across distributed nodes.

- Develop and refine advanced SQL queries to extract, transform, and load data, ensuring accuracy and performance in high-volume production environments.

- Automate routine data tasks and system monitoring using Linux/Unix shell scripting to improve operational efficiency and reduce manual intervention.

- Troubleshoot and resolve performance bottlenecks within the Spark core engine to maintain system stability during peak processing loads.

Required Skillset :

- Demonstrated expertise in building and deploying large-scale data applications using Scala and Apache Spark, with a deep understanding of Spark core internals.

- Strong proficiency in Big Data ecosystem components including Hadoop, HDFS, and YARN, with the ability to manage distributed computing resources effectively.

- Advanced capability in SQL for complex data manipulation and a solid grasp of data modeling principles to support scalable architecture.

- Proven experience in navigating and managing Linux/Unix environments, including shell scripting for automation and system administration.

- Excellent analytical and problem-solving skills, with the ability to communicate technical challenges and solutions clearly to both technical and non-technical stakeholders.

- A minimum of 5 to 8 years of professional experience in Big Data engineering roles, demonstrating a track record of delivering production-grade solutions.

- Ability to work effectively in a remote-first or distributed team environment, maintaining high standards of code quality and collaborative documentation.

- A Bachelors or Masters degree in Computer Science, Information Technology, or a related quantitative field.