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: We are seeking a hands-on Sr. Data Lake/Lakehouse Engineer to design, build, and operate robust data lake and lakehouse solutions that enable analytics, reporting, and AI-driven products. This role will be pivotal in bridging the gap between traditional data warehouses and modern data lakes, ensuring seamless data integration, governance, and accessibility for business intelligence and advanced analytics. Responsibilities: - Design, implement, and maintain scalable data lake and lakehouse architectures using cloud-native services (AWS S3, Glue, Lake Formation, Delta Lake, Snowflake, etc.). - Develop and optimize end-to-end data pipelines (batch and streaming) for ingesting, transforming, and storing structured and unstructured data at scale. - Integrate diverse data sources and ensure efficient, secure, and reliable data ingestion and processing. - Implement and enforce data governance, cataloging, lineage, and access controls (e.g., AWS DataZone / Glue Data Catalog or Unity Catalog, Collibra, Atlan). - Collaborate with cross-functional teams (data scientists, BI engineers, product managers) to translate business needs into reliable, observable, and governed data products. - Drive adoption of modern data engineering frameworks (dbt, Airflow, Delta Live Tables, etc.) and DevOps practices (IaC, CI/CD, automated testing, monitoring). - Champion data quality, security, and compliance (encryption, PII, GDPR, HIPAA, etc.) across all data lake/lakehouse operations. - Mentor and guide team members, contribute to platform roadmaps, and promote best practices in data engineering and lakehouse design. - Stay current with emerging trends in data lakehouse technologies, open-source tools, and cloud platforms. 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: - 10+ years of experience in Data Engineering, Software Engineering, and/or Cloud Engineering, including 5+ years leading data lake or lakehouse transformation initiatives on AWS. - Bachelor’s degree in Computer Science, Data Science, or a related field; Master’s degree preferred. - Experience with cloud data lake architectures and design patterns, including AWS S3, Glue, Lake Formation, Snowflake, raw/curated/consumption zones, Medallion Architecture, data versioning, and schema evolution technologies such as Delta Lake and Apache Iceberg. - Experience with data governance, cataloging, and data management, including Unity Catalog, Collibra, Atlan, AWS Glue Data Catalog, data modeling, data quality, secure data onboarding, and governance practices. - Experience developing production data solutions using Python and/or SQL, including reusable libraries, testing, pipeline orchestration tools such as Airflow, Step Functions, dbt, and both batch and real-time data processing. - Experience with DevOps practices for data platforms, including Terraform/CloudFormation, CI/CD, monitoring, and runbook creation. Preferences: - 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 Core Competencies: - 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) - Excellent communication and stakeholder management skills REF# E0039, E0040 [LPL Global Business Services, LLP - PRIVACY POLICY](https://www.lpl.com/content/dam/edam/culture/people/benefits/global-business-services-job-applicant-privacy-policy.pdf)