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 AVP Tech Lead of Data Warehousing, you will lead a team of data professionals to drive the strategic vision and execution of data warehousing initiatives across the organization. This role is pivotal in leveraging data as a strategic asset to enhance decision-making, drive innovation, and ensure data quality and governance.
Responsibilities:
Partner with existing teams to further develop and implement 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
Mentor and develop a high-performing team of data engineers and analysts, fostering a culture of excellence and continuous learning
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:
Proven track record of leading and developing high performing teams
10+ years of experience in both on-prem and cloud-based data warehousing and data marts, with at least 5 years focused on leadership of Snowflake warehousing team(s)
Bachelor’s degree in Data Science, Computer science or related field; Master’s degree preferred
Demonstrable hands-on experience with:
Cloud data architectures: Snowflake, AWS S3, HVR at minimum. Multi-cloud experience preferred
Data governance and cataloging: including any of the following (preferred experience in multiple tools) Unity Catalog, Collibra, Atlan, AWS Glue Data Catalog
Modern data warehousing: Snowflake, Databricks, Redshift, or equivalent
Programming: Python and/or SQL (production code, reusable libraries, tests)
Pipeline orchestration: Airflow, Step Functions, dbt, or similar
DevOps for data: Terraform/CloudFormation, CI/CD, monitoring, and runbook creation
AI Engineering: Snowflake Coretex, AWS Bedrock, etc.
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
Experience with Spark, Snowflake or other big data frameworks
AWS and/or Snowflake architect or developer certifications
Demonstrated use of AI/ML tools to augment engineering productivity (prompting for code generation, LLMs for docs/tests, query optimization)
Experience with knowledge graphs and semantic data modeling
LLM/AI augmentation tooling
Skills & Tools
AWS (S3, Glue, Lake Formation, IAM), Snowflake
SQL, Python
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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