Data Engineer

Virtusa; Hyderabad, Chennai, Bengaluru; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Virtusa in Hyderabad seeks a Senior Data Engineer to design and deliver real-time and historical data products for complex financial and healthcare platforms. You will build streaming and batch pipelines, integrate domain data, and contribute to semantic modeling and BI reporting.

You will implement data-quality controls, lineage tracking, and reproducibility, and collaborate with data stewards to ensure timely, compliant data processing.

Qualifications

• Typically 5+ years of data engineering experience.
• Experience with Kafka or another event-streaming platform.
• Experience building both batch and streaming data pipelines.

Responsibilities

• Develop stateful and stateless streaming pipelines.
• Implement effective-dated and bitemporal models.
• Build automated controls for data quality, completeness and integrity.
• Capture source-to-target lineage and business transformation lineage.
• Provide point-in-time reproducibility for accounting, actuarial, audit, and regulatory review.
• Optimize data layouts and aggregations for predictable performance.
• Build data pipelines with version-controlled, automated deployment processes.
• Monitor freshness, volume, schema, lineage, quality and latency.

Skills

5+ years data engineering

Kafka or event streaming

Batch and streaming pipelines

Tools

Kafka

dbt

Cube.dev

Job description

Senior Data Engineer

Job family Data Engineering

Recommended level Senior Data Engineer Lead Data Engineer

Position summary

The Senior Data Engineer will build trusted real-time and historical data products for the

Real Time Finance Close and Value-Based Care platform

The role will integrate claims encounters member eligibility provider contract capitation

sub-capitation actuarial journal subledger GL payment and operational data The engineer

will create streaming and batch pipelines that support financial processing, actuarial analysis,

reconciliation Cube.dev semantic models Power BI reporting, ontology integration, and AI-

driven analytics

Support event streaming, APIs, change-data capture, files, databases, and partner

interfaces.

Develop reusable patterns for schema evolution, quarantine, reprocessing, and source-

system reconciliation.

Streaming and transformation engineering

• Develop stateful and stateless streaming pipelines.
• Implement effective-dated and bitemporal models.
• Build automated controls for completeness, validity, uniqueness, timeliness
• consistency, and referential integrity
• Detect missing, duplicate, delayed, and materially changed records
• Capture source-to-target lineage and business transformation lineage
• Provide point-in-time reproducibility for accounting, actuarial, audit, and regulatory
• review
• Work with data stewards to define data-quality thresholds, issue ownership, and
• Optimize data layouts and aggregations for predictable performance

Data platform operations

• Build data pipelines through version-controlled, automated deployment processes
• Monitor freshness, volume, schema, lineage, quality, and processing latency
• Participate in production support, root-cause analysis, replay, and recovery

Required qualifications

• Typically 5 or more years of data engineering experience
• Experience with Kafka or another event-streaming platform
• Experience building both batch and streaming data pipelines

Preferred qualifications

• Experience with temporal, effective-dated, or bitemporal data models
• Familiarity with X12 837/835, HL7, FHIR, or healthcare reference data
• Experience with dbt or an equivalent transformation framework
• Experience with Cube.dev or another governed semantic layer
• Finance and Actuarial can reproduce results for a specific reporting date
• Production pipelines recover safely and predictably after failure