Principal Engineer, Enterprise Data Platform

ESSENTIAL DUTIES AND RESPONSIBILITIES

• Provide strategic direction and technical oversight for a significant greenfield initiative focused on rebuilding and modernizing our data warehouse infrastructure.
• Possessing deep knowledge of data engineering principles, tools, and technologies.
• Providing direction and guidance on data architecture, solution design, and implementation strategies.
• Designing and implementing data pipelines, data warehouse, and data lake using modern technology components like Spark, Iceberg, Delta Lake, Scala, Python etc.
• Implementing and enforcing data governance policies, including data security controls and privacy regulations.
• Define and maintain end to end data flows, Data Lineage, Data Catalog for various data marts
• Be a liaison between solution architects, BSA s and data engineers to ensure compliance to standards of Data integrations, data management and review the data solutions
• Maintain inventory and roadmap of data assets across the Data Platform
• Ensure best practices for data democratization architecture & data virtualization
• Offer insight, guidance, prototype, and direction on the usage of latest trends and technical capabilities for Enterprise Data Management
• Stay updated with the latest industry trends and best practices, sharing knowledge and encourage team to continuously improve their skill s

REQUIRED

• Bachelor s degree or higher in Computer Science or Engineering or related field
• Minimum 15+ years of experience working with Data Management including Data Integration/ETL (Informatica, Talend, Fivetran etc. ), Data Warehouse/Lakes (Oracle, Snowflake, Databricks, Google Big Query, Redshift), Master Data Management, Data Quality, Data Modeling, Data Analytics/BI, Data Enrichment, Security and Governance.
• Minimum of 7+ years of experience focused specifically on Delivery or Solution Architecture of large complex data management programs
• Strong data modeling expertise in supporting both classic and modern data Lakehouse architectures.
• Strong understanding and experience building ELT/ETL solutions
• Experience on various data Quality tools like Informatica Data Quality, Atlan, Collibra, etc.
• Demonstrable experience working with data structures coming from variety of ERP, CRM and other data sources
• Experience working with at least one major cloud data platforms like AWS, Azure, Google, etc.
• Experience working with at least one modern Lakehouse platforms like Databricks, Snowflake, etc.
• Experience working with Tableau, Power BI, or other Data visualization tools. Knowledge of advanced analytics GenAI platforms is a plus.
• Develop Entity Relationship Diagrams using and data modeling tools.
• Guide technical team to tunes complex solutions, monitor system performance, and provide recommendations and means for improvement
• Prototype new technologies and implement innovative solutions to enable teams to consume and understand data faster
• Responsible for metadata management of data domain, inclusive of data definitions, data catalog, data lineage and documentation of data flow for critical processes, Sox compliance
• Partner with Data Governance analyst and Business Data Stewards
• Maintain in-depth understanding of business functions, processes, and relationships as it relates to data

SKILLS

• A solid understanding of data modeling, modern data architecture, master data management, data profiling and data cleansing techniques.
• Experience with REST APIs, GraphQL / OData and Event-Driven Architecture Expertise in SQL with modern data warehousing solutions (e. g. , GBQ, Fabric, Snowflake, Databricks).
• Proficiency in Python and open-source data processing tools (Spark, Parquet, dbt, dataform, etc. )
• Familiarity with essential DevOps practices, including version control, automated CI/CD, etc.
• Ability to analyze, communicate and solve complex problems