"AIA - Coimbatore" Weekend Drive - 31-Oct-2026
Interview Mode - Face to Face
Exp Range - 6 - 8 Years
Location: Coimbatore
Skill: GCP, BigQuery and Python -
Job Summary
GCP Data Engineer
Requirement for N & P program .
Should have strong knowledge in GCP BigQuery and SQL.
Should be proficient with Python or R for data analysis.
Should have Strong knowledge and proven experience of data mining algorithms and statistical analysis.
Should have Ability to interpret complex data and present insights clearly.
Responsibilities
- Design and implement robust data pipelines on cloud platforms using Cloud Composer and Cloud Dataproc to process large scale payer domain datasets with high reliability and performance.
- Develop optimized PySpark and Python code to transform cleanse and aggregate complex healthcare data while maintaining strict data quality and accuracy standards.
- Build efficient data models and schemas in BigQuery and Cloud SQL that support analytics reporting and downstream applications for payer focused use cases.
- Optimize BigQuery queries and storage strategies to reduce cost improve execution time and enhance user responsiveness for business critical workloads.
- Collaborate with product owners data analysts and business stakeholders from the payer domain to translate analytical needs into scalable technical solutions.
- Implement monitoring alerting and automated recovery for Cloud Composer workflows and data pipelines to ensure stability and predictable operations in day to day execution.
- Apply healthcare payer domain knowledge to design data transformations reference mappings and validation rules that align with regulatory clinical and financial requirements.
- Perform code reviews provide constructive feedback and maintain coding standards to ensure maintainable secure and well documented PySpark and Python solutions.
- Troubleshoot production issues across BigQuery Cloud SQL Cloud Composer and Cloud Dataproc environments to restore services quickly and prevent recurrence.
- Create and maintain technical documentation for data flows pipeline configurations and data models to support transparency audit readiness and knowledge sharing.
- Partner with data security and compliance teams to embed privacy access controls and governance practices into all payer data solutions.
- Contribute to continuous improvement by evaluating new cloud features proposing performance enhancements and refining existing data engineering patterns.
- Mentor peers on best practices in cloud based data engineering to uplift team capability and improve delivery quality for payer clients.
Qualifications
- Demonstrate strong hands on experience in designing and developing data pipelines with Cloud Composer and Cloud Dataproc in production grade environments.
- Exhibit advanced proficiency in PySpark and Python for building scalable data processing jobs including tuning and optimization for large healthcare datasets.
- Show proven expertise in BigQuery and Cloud SQL for data modeling query optimization and secure data access suitable for payer analytics scenarios.
- Bring solid understanding of payer domain concepts such as claims eligibility members and providers to design context aware data solutions.
- Display experience working within a hybrid work model and collaborating with distributed teams using agile methods and modern development practices.
- Apply knowledge of data quality testing strategies and version control to deliver reliable well validated and maintainable code for long term use.
コグニザントについて
コグニザント（NASDAQ: CTSH）は、AI Builderおよびテクノロジーサービスプロバイダーとして、お客様にフルスタックのAIソリューションを構築することで、AI投資と企業価値を結ぶ架け橋となっています。業界、ビジネスプロセス、エンジニアリングに関する当社の深い専門知識を活かし、組織固有のビジネス環境をテクノロジー・システムに組み込みます。これにより、人間の可能性を最大限に引き出し、確かな成果を実現するとともに、急速に変化する世界においてグローバル企業が常に一歩先を行くための支援を行っています。 詳細については、cognizant.ai をご覧ください。
雇用に関する追加情報
本募集に記載されている報酬情報は、掲載日時点で正確なものです。Cognizantは、適用される法令に従い、いつでも本情報を変更する権利を留保します。
応募者は、対面またはビデオ会議による面接への参加を求められる場合があります。また、各面接の際に、現在有効な州政府または政府発行の身分証明書の提示を求められる場合があります。
Cognizantは機会均等雇用主です。応募および選考において、人種、肌の色、性別、宗教、信条、性的指向、性自認、国籍、障がい、遺伝情報、妊娠、退役軍人の地位、その他連邦法・州法・地方自治体の法律により保護されるいかなる特性に基づく差別も行いません。
