Evernorth

Healthcare

DataAnalyticsOperationsLeadEngineer-HIH-Evernorth

₹25–40L ~AI est. Hyderabad, India FULL TIME
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Senior candidates.

The Brief

“Data Analytics Operations Lead Engineer -HIH- Evernorth at Evernorth. Skills: Data Engineering, Data Pipelines, Data Lineage, Data Governance. Perform data foundation assessments. Evaluate source system readiness”

Industry & Context.

Healthcare
Problems you'll solve

Identify issues; Remediate issues; Troubleshoot issues

What They're Looking For.

Must Have

5–8 years of experience, Databricks experience, Lakehouse architectures experience, Enterprise-grade data pipelines, Data platform integrations, Data governance tools integrations, Technical lineage publishing, Metadata publishing, Data observability controls, Data reliability controls, Enterprise data integration patterns, Enterprise data governance patterns

Nice to Have

Platinum / Tier-0 / certified data products, Collibra APIs, Metadata ingestion frameworks, Lineage automation patterns, Regulated environments experience, Compliance-driven environments experience, DataOps organization experience, Product-oriented data organization experience

What You'll Do.

Perform data foundation assessments

Evaluate source system readiness

Evaluate integration patterns

Evaluate data model structure

Evaluate data reuse potential

Evaluate reliability controls

Evaluate scalability controls

Evaluate quality controls

Design data pipelines

Maintain data pipelines

Meet performance standards

Meet availability standards

Meet operational resilience standards

Implement technical data lineage

Maintain technical data lineage

Maintain integrations

Publish technical metadata

Associate data assets

Enable certification workflows

Enable impact analysis workflows

Align engineered metadata

Design automated observability

Design reliability reporting

Monitor pipeline health

Integrate observability outputs

Remediate data quality issues

Remediate operational issues

Optimize transformations

Support curated data layers

Translate data specifications

Translate lineage requirements

Translate business metadata

Ensure data assets fit reporting

Ensure data assets fit metrics

Ensure data assets fit analytics

Implement enterprise standards

How You'll Work.

Team & Collaboration

Data Operations Analysts; DataOps teams; Governance teams; Analytics teams; Platform teams; Architecture teams

Full Job Description

**Lead Data Engineer – Platinum Data Foundations, Lineage & Observability** **Experience Level** **5–8 years** in Data Engineering, Analytics Engineering, or Enterprise Data Platforms **Role Summary** The Senior Data Engineer is responsible for building, assessing, and strengthening the **data foundations** that support **Platinum‑level enterprise data sources**. This role works in close partnership with Data Operations Analysts to operationalize data specifications, implement lineage and observability capabilities, and ensure critical enterprise data assets are reliable, transparent, and governed. A key component of this role is **engineering integrations between Platinum data products and enterprise data governance platforms (e.g., Collibra)** to automate lineage, technical metadata, and observability signals across the data ecosystem. **Key Responsibilities** **Platinum Data Foundation Engineering** * Partner with Data Operations Analysts to perform **data foundation assessments** for Platinum data sources, evaluating: * Source system readiness and integration patterns * Data model structure and reuse potential * Reliability, scalability, and quality controls * Design, build, and maintain **enterprise‑grade data pipelines** that support certified data products. * Ensure Platinum sources meet standards for **performance, availability, and operational resilience**. **Data Lineage, Governance & Architecture Enablement** * Implement and maintain **end‑to‑end technical data lineage** from source systems through Databricks and downstream consumption layers. * **Build and maintain integrations between data products and enterprise data governance tools (e.g., Collibra)** to: * Publish technical metadata and lineage * Associate data assets with governed business metadata * Enable automated certification and impact analysis workflows * Partner with DataOps and governance teams to ensure engineered metadata aligns with enterprise standards and stewardship processes. **Data

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