Software Engineering Lead Analyst - HIH - Evernorth

Location: Hyderabad, India

Remote Type: Hybrid

Time Type: Full time

Job Description

Software Engineering Lead Analyst
 

Position Overview

Evernorth, a leading Health Services company, is looking for a Software Engineering Lead Analyst to help design, build, and run enterprise data de-identification/masking solutions. This role is focused on delivering safe, compliant, and useful non-production data by applying masking rule sets while preserving data utility and maintaining data relationships (e.g., consistent treatment of key identifiers across tables and domains).

You will work in an agile environment to automate repeatable data movement and masking workflows end-to-end: connect to platforms such as Databricks and traditional relational databases, extract and transform data into required layouts/formats, submit jobs to Delphix for de-identification, and deliver masked outputs to downstream destinations. The ideal candidate brings strong database fundamentals, a practical understanding of how applications use data, and the ability to orchestrate dependable processes (including error handling, logging, monitoring, and audit-ready evidence).

Roles & Responsibilities

• Design and implement data masking/de-identification solutions (rule sets, profiling, execution, validation), with an emphasis on preserving data utility and maintaining data relationships across tables.
• Build and maintain automated pipelines that extract/transform data (Python/SQL), submit masking jobs to Delphix, and publish masked datasets to target environments (e.g., Databricks, relational databases, files/object storage).
• Orchestrate and schedule workflows using automation/orchestration tooling (e.g., CloudBees), including dependency management, retries, notifications, and operational runbooks.
• Partner with application teams, data owners/stewards, and security/compliance stakeholders to identify sensitive fields, define masking requirements, and ensure implementations meet policy and audit expectations.
• Produce and maintain technical documentation for data flows, data mappings, masking logic, and operational evidence (logs/metrics) to support troubleshooting and compliance audits.

Qualifications

Required Experience & Education: 

• 5 - 8 years of relevant experience in data engineering, data platform engineering, or data protection (masking/de-identification).
• Hands-on experience building repeatable, production-grade data pipelines (extract, transform, load/publish), including controls for logging, monitoring, and failure recovery.
• Experience in data engineering or analytics using platforms like Databricks and Snowflake (or similar lakehouse/warehouse technologies).
• Strong experience with relational databases and SQL (e.g., Oracle, Teradata, SQL Server) and familiarity with NoSQL databases (e.g., MongoDB).
• Very strong understanding of database concepts and data relationships (keys, constraints, joins, lineage), including strategies to preserve referential integrity across masked datasets.
• Experience with orchestration/automation platforms (e.g., CloudBees or similar CI/CD or scheduling tools) to run and manage data workflows.
• Hands-on experience with Python for data processing and automation (including connecting to databases/lakehouse platforms, transforming datasets, and integrating with APIs).
• Hands-on experience with data masking/de-identification approaches and tooling; Delphix experience (Continuous Compliance / Masking Engine) is strongly preferred.
• Excellent problem-solving skills and the ability to analyze complex issues and implement effective solutions.

Required Skills:

• Advanced SQL and data modeling concepts; strong understanding of relational data structures; Delphix (masking/de-identification and/or virtualization) experience.
• Python automation; workflow orchestration (e.g., CloudBees); and basic cloud experience (AWS/Azure) for connecting to data services and managing credentials/access patterns.

Preferred Skills, Experience & Education:

• Familiarity with IBM mainframe concepts (e.g., DB2, JCL) and/or the BMC toolset (e.g., File-AID/RDX, Data Privacy) is a plus (not required); cloud certification (AWS Cloud Practitioner or similar) and AI/ML exposure are also beneficial.

About Evernorth Health Services