Assistant Manager

GCP Cloud Analytics Engineer – Job description

Role and Responsibilities:

We’re looking for a GCP Cloud Analytics Engineer with strong HEOR/RWE/US Healthcare domain experience and hands-on expertise in GCP, Python/PySpark, AI & ML to design and build scalable data pipelines and applications on cloud-native ecosystem. You’ll work on automation, high-volume data systems, driving data and analytics teams.

• Design, develop and maintain ETL data pipelines using BigQuery, SQL and Python/Pyspark
• Process and transform large-scale structured and unstructured datasets cleaning, preprocessing, and feature engineering using advanced ML algorithms.
• Analyze, understand and migrate existing ETL processes from SAS to BigQuery/ Python/PySpark
• Develop workflows for data ingestion, transformation, and loading on GCP (BigQuery, Cloud Storage, Dataflow)
• Generate effective data visualizations and insights using Tableau/PowerBI
• Ensure data quality, consistency and reliability during migration and in production pipelines

Required Qualifications:

• 3+ years of Experience in ETL development, Data Engineering, Data Management with strong focus on GCP, SQL, Python/Pyspark and AI/ML for building production ready Python-based AI/ML pipelines and APIs for integration with production systems.

• Strong HEOR/RWE/Clinical Trials or US healthcare data (medical/pharmacy claims, Labs and enrollment data.

• Strong understanding of data preprocessing, feature selection, and model evaluation techniques. Apply ML/DL frameworks (e.g., TensorFlow, PyTorch, Keras) for NLP, and predictive analytics.
• Strong hands-on experience with GCP BigQuery, Data Proc, Airflow DAG, Dataflow, GCS, Pub/sub, Secret Manager, Cloud Functions, Beams, CI/CD workflows, Git.
• Strong data visualization skills with Tableau/PowerBI.
• Good understanding of SAS/SQL data step logic and procedures; experience in migrating ETL jobs from SAS to Python
• Strong problem solving and communication skills.
• Good understanding of Generative AI and LLM fine-tuning.
• Familiar with cloud AI services (AWS, Azure ML/AI Platform) is a plus.