Data Engineer + Healthcare

Role Overview

We are seeking a highly skilled Healthcare Data & Analytics Consultant with strong domain expertise in US healthcare (payer/provider) and sharp analytical problem-solving capabilities. The ideal candidate will bring deep understanding of healthcare operations along with hands-on experience in data engineer, data analysis, forecasting, AI/ML concepts, and translating healthcare business problems into data-driven solutions.

This role is ideal for someone who is healthcare-first, with analytics as a strong secondary capability.

Key Responsibilities

· Translate healthcare-specific business needs into clear analytical problem statements and data requirements.

· Support solution design for healthcare use cases such as risk stratification, forecasting utilization/costs, quality metrics, operational performance, and member/patient outcomes.

· Perform hands-on data exploration and validation using SQL and BI tools.

· Support analytics workstreams involving trend analysis, segmentation, KPI development, dashboards, and insight generation.

· Partner with data science teams to incorporate domain logic into AI/ML models, ensuring clinical/operational relevance.

· Work closely with cross-functional SMEs, product owners, and architecture/analytics teams to shape healthcare analytics solutions.

· Participate in requirement workshops, business discussions, and client demos.

· Conduct root cause analysis for data or process issues impacting healthcare metrics or claim outcomes.

· Prepare clear documentation: BRDs, data dictionaries, dashboards, analytical summaries, and business recommendations.

Required Skills & Qualifications

· 3 + years of experience in healthcare domain roles, preferably US healthcare (payer/ provider).

· Strong understanding of claims, benefits, eligibility, care management, UM/CM, member/provider workflows.

· Hands-on experience with Python

· hands on SQL-based data validation, datasets, and healthcare data models (claims, membership, provider, clinical).

· Strong analytical mindset with experience in basic ML/AI concepts, forecasting or trend modelling, exploratory data analysis (EDA), KPI building and insight generation

· Excellent communication, consulting, and stakeholder engagement skills.

Preferred Qualifications

· Experience working with US healthcare payers, providers, or large hospital systems.

· Knowledge of healthcare regulations (HIPAA, CMS, Medicare/Medicaid, HEDIS, quality measures).

· Exposure to data science workflows, feature engineering, prediction models, or AI-enabled decision tools.

· Experience supporting forecasting use cases such as cost forecasting, utilization forecasting, staffing/demand models, chronic condition progression, or operational prediction models.

· hands on with Pyspark

· Familiarity with healthcare interoperability standards (FHIR, HL7).