Company Overview :

Sysmind is a global technology services firm specializing in digital transformation, cloud engineering, and data analytics. We partner with enterprises across the healthcare, finance, and retail sectors to build scalable infrastructure and data-driven solutions. With a focus on high-performance engineering, we help our clients navigate complex technical landscapes by deploying robust, cloud-native architectures that drive operational efficiency and business intelligence at scale.

Role Overview :

As a Senior Data Engineer based in Pune, you will serve as a technical lead responsible for designing and maintaining the data pipelines that power our clients' analytical ecosystems. You will collaborate closely with data scientists, product managers, and infrastructure teams to transform raw data into actionable insights. Your work will directly influence the reliability and performance of large-scale data platforms, ensuring that business stakeholders have seamless access to high-quality, governed data to support critical decision-making processes.

Key Responsibilities :

- Architect and maintain scalable ETL/ELT pipelines to process large volumes of structured and unstructured data for diverse business requirements.

- Optimize data warehouse performance and query efficiency to ensure rapid data retrieval for internal and external stakeholders.

- Design robust data models that support complex analytical reporting and machine learning initiatives across the organization.

- Implement automated data quality checks and monitoring frameworks to maintain high standards of data integrity and reliability.

- Mentor junior engineering team members by conducting code reviews and promoting best practices in software development and data architecture.

- Collaborate with cloud infrastructure teams to manage and scale Big Data environments, ensuring cost-effectiveness and high availability.

Required Skillset :

- Demonstrated expertise in building complex data pipelines using Python and SQL within large-scale production environments.

- Advanced proficiency in Big Data technologies, specifically Spark and Hadoop, with a proven ability to process petabyte-scale datasets.

- Strong hands-on experience in cloud-based data warehousing and ETL orchestration using AWS services.

- Ability to translate complex business requirements into technical specifications and communicate architectural decisions to non-technical stakeholders.

- Proven track record of working in a collaborative, hybrid work environment, demonstrating strong self-management and team-oriented communication.

- A Bachelors or Masters degree in Computer Science, Engineering, or a related quantitative field, supported by 10 to 12 years of relevant professional experience in data engineering.