Engineer II, Data Warehouse

LPL Financial · Banking & Financial Services

Hyderabad
On-site
Posted today
Apply by 28 Oct
Data & AI

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About the job

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:

As an Engineer II in Data Warehousing & Automation Engineering , you will partner with a team of data professionals to deliver data warehousing initiatives across the LPL Financial. This role is pivotal in leveraging data as a strategic asset to enhance decision-making, drive innovation, and ensure data quality and governance.

Responsibilities:

Develop solutions to deliver on the data warehousing strategy, ensuring alignment with business objectives and driving data-driven decision-making across the organization

Oversee the integration of data products in Snowflake and dbt, ensuring seamless data flow, quality and accessibility

Design and develop data replication and transformation pipelines leveraging solutions such as HVR. Configure and manage HVR instances for optimal performance and scalability

Develop, automate and implement data quality checks and monitoring procedures

Manage and optimize Snowflake data warehouse, data mart and application-based solutions to ensure high performance, scalability, and reliability

Implement cost management strategies to optimize data warehousing expenses while maintaining high service levels

Ensure data security, compliance, and governance are integrated into all data warehousing processes to meet regulatory and organizational standards

Establish and maintain robust metadata management practices to ensure data quality and accessibility

Work closely with cross-functional teams, including IT, marketing, and customer service, to ensure data warehousing initiatives support business goals

Emphasize rapid prototyping and continuous process improvement to enhance data warehousing capabilities and drive innovation

Stay up-to-date on the latest advancements in industry and technology solutions, bringing insights to the team for continuous development of our stack, solutions and ways of working

What are we looking for?

We’re looking for strong collaborators who deliver exceptional client experiences and thrive in fast-paced, team-oriented environments. Our ideal candidates pursue greatness , act with integrity , and are driven to help our clients succeed . We value those who embrace creativity, continuous improvement, and contribute to a culture where we win together and create and share joy in our work.

Requirements:

7+ years of experience in both on-prem and cloud-based data warehousing and data marts, with at least 4 years focused on leadership of warehousing team(s)

Bachelor’s degree in Data Science, Computer science or related field; Master’s degree preferred

Demonstrable hands-on experience with:

Snowflake, AWS S3 at minimum.

Data governance and cataloging

Programming: Python and/or SQL (production code, reusable libraries, tests)

Pipeline development and orchestration: HVR, Airflow, Step Functions, dbt and others

DevOps for data: Terraform/CloudFormation, CI/CD, monitoring, and runbook creation

Strong understanding of data modeling, data quality, and secure data onboarding/governance

Experience with both batch and real-time data processing

Core Competencies :

Excellent communication and stakeholder management skills

Preferences:

Snowflake developer certifications

AI Engineering: Snowflake Coretex, AWS Bedrock, etc.

Demonstrated use of AI/ML tools to augment engineering productivity (prompting for code generation, LLMs for docs/tests, query optimization)

Skills & Tools

AWS (S3, Glue, Lake Formation, IAM), Snowflake

SQL, Python

HVR, dbt, Airflow, Step Functions

Terraform/CloudFormation, CI/CD (GitHub Actions, Jenkins)

Observability (Dynatrace preferred, Datadog, Prometheus)

Data governance & security (Unity Catalog, Collibra, Atlan)

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