Sr Engineer, Data Analytics Engineering
- Compensation
- Not disclosed
- Location
- Hyderabad
- Work setup
- Not specified
- Seniority
- Senior
- Employment
- Not specified
- Experience
- 8+ years
- Category
- Data analytics
- Posted
Skills
Must have
- Proven track record of leading and developing high performing, engaged teams.
- 8+ years of experience in data engineering, software engineering, and/or cloud engineering.
- Bachelor’s degree in Data Science, Computer science or related field; Master’s degree preferred.
- Demonstrable hands-on experience with: Cloud data lake architectures: AWS S3, Glue, Lake Formation, Snowflake, or similar. Data lake design patterns: raw, curated, consumption zones; medallion archite
- Strong understanding of data modeling, data quality, and secure data onboarding/governance.
- Experience with both batch and real-time data processing.
Full description
Where Ambition Meets Innovation
At LPL’s Global Capability Center, you'll find a collaborative culture where your voice matters, integrity guides every decision, and technology fuels progress. Your skills, talents, and ideas will redefine what's possible. LPL's success reflects its exceptional employees, who together pursue one noble purpose: empowering financial advisors to deliver personalized advice for all who need it. We’re proud to be expanding and reaching new heights in Hyderabad.
Join us as we create something extraordinary together.
Job Overview:
The Senior Data Analytics Engineer is a critical member of the Data Modernization & Integration organization. This exceptional developer will be responsible for leading a high performing team responsible for designing, building, and modernizing the ingestion, integration, and API services that power LPL’s cloud data ecosystem.
This role drives the transformation of legacy data feeds into scalable, governed, cloud-native pipelines and helps define the engineering standards that support LPL’s federated data product operating model. The ideal candidate combines deep hands-on engineering expertise with strong architectural instincts, a passion for automation, and the ability to collaborate across platform, analytics, and AI teams.
Responsibilities:
Modernization & Cloud Engineering
- Architect and lead migration of legacy SQL/SSIS/ETL pipelines into AWS-native ingestion and integration patterns.
- Design and implement scalable batch, streaming, and event-driven pipelines using services such as S3, Glue, Lambda, Kinesis, DynamoDB, and Step Functions.
- Build resilient data movement frameworks with embedded governance (metadata, lineage, security, quality).
- Contribute to decommissioning efforts by rationalizing and replacing legacy pipeline assets.
Integration & API Engineering
- Develop secure, performant APIs using modern tooling (API Gateway, Lambda, GraphQL, REST).
- Standardize integration patterns for reusable ingestion modules and domain onboarding.
- Partner with Enterprise Architecture to align on API standards, patterns, and best practices.
Automation & Platform Enablement
- Implement infrastructure-as-code using tools like Terraform or CloudFormation.
- Develop CI/CD pipelines promoting automation, repeatability, and quality.
- Contribute to shared libraries, frameworks, and templates that accelerate onboarding of new data sources.
- Drive observability improvements through logging, metrics, tracing, and automated alerting.