01Overview
Company Detail:
Founded in 2015, Healthark began as a healthcare and life sciences consulting firm and is rapidly transforming into a tech-first organization specializing in Data Engineering, Data Science, Analytics, Generative AI, and Intelligent Automation.
We are a cross-disciplinary team that fuses deep healthcare domain expertise with cutting-edge technological capabilities to tackle complex, data-driven challenges across the healthcare ecosystem. Our services span Growth and GCC Advisory, Real-World Evidence (RWE), digital health innovation, AI/ML solutioning, and the development of modern data platforms.
With a team of 150+ consultants, data scientists, engineers, and healthcare experts, we have delivered over 1000 high-impact projects across 60+ global markets. Our clientele includes nimble startups as well as global healthcare and life sciences leaders.
From our innovation hubs in Ahmedabad, Bangalore, and Hyderabad, Healthark is driving the next wave of healthcare transformationleveraging scalable data platforms, automation frameworks, and GenAI-powered insights to deliver measurable outcomes.
Position: Sr Pyspark Developer
Experience: 6+ years
Location: Hyderabad, Bengaluru, Chennai,Pune
Work Mode: Hybrid
Working Hours: 10:00 AM to 07:00 PM
Working Days: Mon to Fri
Company Url: https://healtharkinsights.com/
About the Role
We are looking for a highly skilled Senior Data Engineer PySpark with strong expertise in designing, developing, and optimizing large-scale data processing solutions. The ideal candidate will have hands-on experience with PySpark, Python, SQL, and Google BigQuery, along with a strong understanding of modern data engineering practices, ETL/ELT pipelines, and cloud-based data platforms.
Key Responsibilities
Design, develop, and maintain scalable data pipelines using PySpark and Python.
Build and optimize Spark-based ETL/ELT workflows for processing large volumes of structured and semi-structured data.
Develop productive SQL queries and data models to support analytics and reporting requirements.
Design and manage data solutions using Google BigQuery.
Optimize Spark jobs for performance, scalability, and resource utilization.
Ensure data quality, governance, observability, and reliability across the data platform.
Troubleshoot complex data processing issues and implement performance improvements.
Collaborate with data architects, analysts, product teams, and business stakeholders to deliver robust data solutions.
Participate in code reviews and follow software engineering best practices.
Work in an Agile environment, contributing to sprint planning, development, testing, and deployment.
Required Skills
Strong hands-on experience with PySpark, Python, and SQL.
Extensive experience designing and optimizing Spark-based ETL/ELT pipelines and distributed data processing jobs.
Strong understanding and hands-on experience with Google BigQuery.
Experience working with large-scale datasets and distributed computing frameworks.
Strong knowledge of data quality, data governance, observability, and performance tuning.
Good understanding of data engineering best practices and scalable architecture.
Strong analytical, debugging, and problem-solving skills.
Excellent communication and collaboration skills.
Experience working in Agile/Scrum development environments.
Qualifications
Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or a related field.
6+ years of experience in Data Engineering with strong expertise in PySpark and large-scale data processing.
Preferred Skills
Experience with cloud platforms such as Google Cloud Platform (GCP).
Knowledge of data orchestration tools such as Apache Airflow.
Familiarity with Git, CI/CD pipelines, and DevOps practices.
Exposure to data warehousing, data lakes, and modern analytics architectures. .
